Forward Deployed Engineer
Lafayette, LA · On-site
Running AI/ML workloads for training and inference on AWS, Azure, or GCP (e.g., SageMaker, Azure ML, Vertex AI) . Processing and managing large scale (TB scale) datasets and their associated data ...
Forward Deployed Engineer
Lafayette, LA · On-site
Running AI/ML workloads for training and inference on AWS, Azure, or GCP (e.g., SageMaker, Azure ML, Vertex AI) . Processing and managing large scale (TB scale) datasets and their associated data ...
Google AI Lead Architect
New Orleans, LA · On-site
$53 - $72.75/hr
Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...
Google AI Lead Architect
New Orleans, LA · On-site
$53 - $72.75/hr
Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...
Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...
Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...
Senior AI Scientists
New Orleans, LA · On-site
Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...
Senior AI Scientists
New Orleans, LA · On-site
Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Experience with model serving, inference optimization, and production deployment. ML Engineering / Platform Mindset * Strong background in building scalable, production-grade systems with focus on ...
Experience with model serving, inference optimization, and production deployment. ML Engineering / Platform Mindset * Strong background in building scalable, production-grade systems with focus on ...
$116K - $150K/yr
... inference workloads, utilization patterns, and long-term AI operating economics. * Lead value ... Solid understanding of modern data platforms, distributed systems, and AI/ML workloads, including ...
$116K - $150K/yr
... inference workloads, utilization patterns, and long-term AI operating economics. * Lead value ... Solid understanding of modern data platforms, distributed systems, and AI/ML workloads, including ...
Ml Inference information
What is a $900000 AI job?
A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.
What is ML inference?
ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.
What is the difference between Ml Inference vs Data Scientist?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research institutions, tech firms, consulting |
ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.
What engineer makes $500,000 a year?
Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.
Which 3 jobs will survive AI?
Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.
What are some common challenges faced by ML Inference Engineers when deploying models to production?
ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.
Will MLE be replaced by AI?
Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.
What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?
To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Louisiana? For Ml Inference jobs in Louisiana, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Louisiana look for? The top searched job categories for Ml Inference jobs in Louisiana are:
What cities in Louisiana are hiring for Ml Inference jobs? Cities in Louisiana with the most Ml Inference job openings:
CGI rating
7.1
Based on 19 frontline employees who took The Breakroom Quiz
146th of 220 rated it services
Job description
Forward Deployed Engineer
Category: Software Development/ Engineering
Main location: United States, Louisiana, Lafayette
Position ID:J0726-1326
Employment Type: Full Time
U.S. - The best version of me
By playing this video you consent to Google/YouTube processing your data and using cookies - Learn more.
Position Description:
The best version of us starts with You!
We CGI looking for Forward Deployed Engineer. With your expertise, you will work with a high performing team to consult and develop solutions for a major client.
As a Forward Deployed Engineer (FDE), you will embed directly with the client's teams to take proof of concept (PoC) initiatives the client has already shortlisted and turn them into working software: validating technical feasibility, hardening the solution into a Minimum Viable Product (MVP), running a scoped pilot, and then partnering with the client's Enterprise Architecture team to roll the solution out across the organization.
This position is located on-site in Lafayette, LA (Preferred), Bloomfield, CT, Raleigh, NC or in a Hybrid working Model.
Your future duties and responsibilities:
. Partner in an embedded, on site/hybrid capacity with the client to take ownership of PoCs the client has already shortlisted and approved for further investment.
. Perform technical due diligence on each PoC, assessing architecture, data flows, integration points, and the gap between prototype and production grade software.
. Serve as the primary technical point of contact between the client and CGI, providing regular updates on PoC/MVP/pilot progress, risks, and decisions needed.
. Partner with CGI's AI/solution architects on solutioning: validating technical approach, leveraging reusable accelerators and best practices, and escalating architecture or design decisions as needed.
. Scale validated PoCs into MVPs, building in the engineering rigor (testing, CI/CD, monitoring, security controls) required to support real users.
. Design and execute pilot programs to validate MVPs with a limited user base, gather feedback, and define success criteria and exit conditions.
. Collaborate closely with the client's Enterprise Architecture team to align each solution's target state architecture, technology standards, and governance requirements.
. Develop and execute org wide scaling and rollout plans in partnership with Enterprise Architecture, covering migration approach, integration with existing systems, change management, and knowledge transfer.
. Act as the technical bridge between the client's business/product stakeholders and delivery/engineering teams, translating shortlisted ideas into actionable delivery plans.
. Identify technical risks, dependencies, and reusable platform components across multiple PoC to scale efforts.
. Produce documentation, runbooks, and architecture artifacts to support handoff to steady state operations teams.
. Mentor and support client and delivery teams on best practices for rapid prototyping, MVP engineering, and phased scaling.
. Design, build, and maintain computer vision pipelines that analyze and extract insights from large volumes of images at scale.
. Architect and run AI workloads for both training and inference on cloud platforms such as AWS, Azure, or GCP, optimizing for cost, scalability, and performance.
. Develop automation and tooling using Python for data preprocessing, model training, deployment, and monitoring.
. Collaborate with cross functional teams to translate complex business problems into machine learning solutions that guide prediction and forecasting.
. Address the challenges of building, deploying, and scaling production grade computer vision systems, including data quality, model accuracy, latency, and throughput.
. Monitor model performance in production and implement retraining and continuous improvement (MLOps) workflows.
Required qualifications to be successful in this role:
At least 7+ years of professional software engineering experience in:
. Hands on experience with at least one major cloud platform (AWS, Azure, or GCP) and modern DevOps practices.
. Computer vision and deep learning frameworks (e.g., PyTorch, TensorFlow, OpenCV)
. Building, training, and fine-tuning image processing and deep learning models (classification, detection, segmentation)
. Python for ML development, data processing, and automation
. Running AI/ML workloads for training and inference on AWS, Azure, or GCP (e.g., SageMaker, Azure ML, Vertex AI)
. Processing and managing large scale (TB scale) datasets and their associated data pipelines
. Building and scaling production ML systems, including MLOps practices such as model deployment, monitoring, and retraining.
. Hands on software/platform engineering experience, including direct experience taking prototypes or PoCs into production.
. Demonstrated experience scaling a PoC into an MVP and carrying it through a pilot to broader production rollout.
. Strong full stack or platform engineering background, including cloud architecture, APIs, data integration, and CI/CD.
. Experience working directly with enterprise architecture teams and standards, translating architectural guidance into working implementations.
Good to Have / Bonus Skills:
. Distributed and multi GPU training and GPU optimization (e.g., CUDA)
. Containerization and orchestration for ML workloads (Docker, Kubernetes)
. Large scale data engineering tools (e.g., Spark, Databricks) for image and data processing
. MLOps tooling (e.g., MLflow, Kubeflow, SageMaker Pipelines) and predictive/forecasting models
Education: Bachelor's degree in computer science or related field.
#LI-ARK1
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $71,700.00 $141,100.00.
CGI's benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation, holidays, and sick time
. Paid parental leave
. Learning opportunities and tuition assistance
. Wellness and Well-being programs
Skills:
What you can expect from us:
Together, as owners, let's turn meaningful insights into action.
Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you'll reach your full potential because...
You are invited to be an owner from day 1 as we work together to bring our Dream to life. That's why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company's strategy and direction.
Your work creates value. You'll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.
You'll shape your career by joining a company built to grow and last. You'll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
Come join our team-one of the largest IT and business consulting services firms in the world.
Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned.
We make it easy to translate military experience and skills! Click here to be directed to our site that is dedicated to veterans and transitioning service members.
All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances.
CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGI's legal duty to furnish information.
Category: Software Development/ Engineering
Main location: United States, Louisiana, Lafayette
Position ID:J0726-1326
Employment Type: Full Time
U.S. - The best version of me
By playing this video you consent to Google/YouTube processing your data and using cookies - Learn more.
Position Description:
The best version of us starts with You!
We CGI looking for Forward Deployed Engineer. With your expertise, you will work with a high performing team to consult and develop solutions for a major client.
As a Forward Deployed Engineer (FDE), you will embed directly with the client's teams to take proof of concept (PoC) initiatives the client has already shortlisted and turn them into working software: validating technical feasibility, hardening the solution into a Minimum Viable Product (MVP), running a scoped pilot, and then partnering with the client's Enterprise Architecture team to roll the solution out across the organization.
This position is located on-site in Lafayette, LA (Preferred), Bloomfield, CT, Raleigh, NC or in a Hybrid working Model.
Your future duties and responsibilities:
. Partner in an embedded, on site/hybrid capacity with the client to take ownership of PoCs the client has already shortlisted and approved for further investment.
. Perform technical due diligence on each PoC, assessing architecture, data flows, integration points, and the gap between prototype and production grade software.
. Serve as the primary technical point of contact between the client and CGI, providing regular updates on PoC/MVP/pilot progress, risks, and decisions needed.
. Partner with CGI's AI/solution architects on solutioning: validating technical approach, leveraging reusable accelerators and best practices, and escalating architecture or design decisions as needed.
. Scale validated PoCs into MVPs, building in the engineering rigor (testing, CI/CD, monitoring, security controls) required to support real users.
. Design and execute pilot programs to validate MVPs with a limited user base, gather feedback, and define success criteria and exit conditions.
. Collaborate closely with the client's Enterprise Architecture team to align each solution's target state architecture, technology standards, and governance requirements.
. Develop and execute org wide scaling and rollout plans in partnership with Enterprise Architecture, covering migration approach, integration with existing systems, change management, and knowledge transfer.
. Act as the technical bridge between the client's business/product stakeholders and delivery/engineering teams, translating shortlisted ideas into actionable delivery plans.
. Identify technical risks, dependencies, and reusable platform components across multiple PoC to scale efforts.
. Produce documentation, runbooks, and architecture artifacts to support handoff to steady state operations teams.
. Mentor and support client and delivery teams on best practices for rapid prototyping, MVP engineering, and phased scaling.
. Design, build, and maintain computer vision pipelines that analyze and extract insights from large volumes of images at scale.
. Architect and run AI workloads for both training and inference on cloud platforms such as AWS, Azure, or GCP, optimizing for cost, scalability, and performance.
. Develop automation and tooling using Python for data preprocessing, model training, deployment, and monitoring.
. Collaborate with cross functional teams to translate complex business problems into machine learning solutions that guide prediction and forecasting.
. Address the challenges of building, deploying, and scaling production grade computer vision systems, including data quality, model accuracy, latency, and throughput.
. Monitor model performance in production and implement retraining and continuous improvement (MLOps) workflows.
Required qualifications to be successful in this role:
At least 7+ years of professional software engineering experience in:
. Hands on experience with at least one major cloud platform (AWS, Azure, or GCP) and modern DevOps practices.
. Computer vision and deep learning frameworks (e.g., PyTorch, TensorFlow, OpenCV)
. Building, training, and fine-tuning image processing and deep learning models (classification, detection, segmentation)
. Python for ML development, data processing, and automation
. Running AI/ML workloads for training and inference on AWS, Azure, or GCP (e.g., SageMaker, Azure ML, Vertex AI)
. Processing and managing large scale (TB scale) datasets and their associated data pipelines
. Building and scaling production ML systems, including MLOps practices such as model deployment, monitoring, and retraining.
. Hands on software/platform engineering experience, including direct experience taking prototypes or PoCs into production.
. Demonstrated experience scaling a PoC into an MVP and carrying it through a pilot to broader production rollout.
. Strong full stack or platform engineering background, including cloud architecture, APIs, data integration, and CI/CD.
. Experience working directly with enterprise architecture teams and standards, translating architectural guidance into working implementations.
Good to Have / Bonus Skills:
. Distributed and multi GPU training and GPU optimization (e.g., CUDA)
. Containerization and orchestration for ML workloads (Docker, Kubernetes)
. Large scale data engineering tools (e.g., Spark, Databricks) for image and data processing
. MLOps tooling (e.g., MLflow, Kubeflow, SageMaker Pipelines) and predictive/forecasting models
Education: Bachelor's degree in computer science or related field.
#LI-ARK1
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $71,700.00 $141,100.00.
CGI's benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation, holidays, and sick time
. Paid parental leave
. Learning opportunities and tuition assistance
. Wellness and Well-being programs
Skills:
- Validation
- Amazon Web Services Cloud
- Azure
- Embedded Software Development
- Enterprise architecture
- Google Cloud Platform
- Stakeholder management
- Systems Architecture
- Artificial Intelligence
- Python
- PyTorch
What you can expect from us:
Together, as owners, let's turn meaningful insights into action.
Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you'll reach your full potential because...
You are invited to be an owner from day 1 as we work together to bring our Dream to life. That's why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company's strategy and direction.
Your work creates value. You'll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.
You'll shape your career by joining a company built to grow and last. You'll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
Come join our team-one of the largest IT and business consulting services firms in the world.
Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned.
We make it easy to translate military experience and skills! Click here to be directed to our site that is dedicated to veterans and transitioning service members.
All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances.
CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGI's legal duty to furnish information.