Machine Learning Engineer
Shelton, CT · On-site
Our global engineering teams work collaboratively to develop step-change technologies that define ... machine learning models or statistical analyses into production and keeping them running • ...
Machine Learning Engineer
Shelton, CT · On-site
Our global engineering teams work collaboratively to develop step-change technologies that define ... machine learning models or statistical analyses into production and keeping them running • ...
Machine Learning Engineer
Shelton, CT · On-site
Machine Learning Engineer Sperry Rail, Inc. Shelton, Connecticut, United States About this position About Sperry: Sperry Rail is on a mission-critical journey to revolutionize the Rail Flaw Detection ...
Machine Learning Engineer
Shelton, CT · On-site
Machine Learning Engineer Sperry Rail, Inc. Shelton, Connecticut, United States About this position About Sperry: Sperry Rail is on a mission-critical journey to revolutionize the Rail Flaw Detection ...
Machine Learning Engineer
Shelton, CT · On-site
$56 - $74/hr
You are the engineer. What the other two build in notebooks, you turn into systems that run on a ... Experience putting machine learning models or statistical analyses into production and keeping them ...
Machine Learning Engineer
Shelton, CT · On-site
$56 - $74/hr
You are the engineer. What the other two build in notebooks, you turn into systems that run on a ... Experience putting machine learning models or statistical analyses into production and keeping them ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
Machine Learning Engineer
Waterbury, CT · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
Machine Learning Engineer
Waterbury, CT · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
Machine Learning Engineer
Norwalk, CT · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
Machine Learning Engineer
Norwalk, CT · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
Freelance Google Machine Learning Engineer information
What does a freelance Google Machine Learning Engineer do?
A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.
What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?
To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.
What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?
Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.
What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?
| Aspect | Freelance Google Machine Learning Engineer | Freelance Data Scientist |
|---|---|---|
| Credentials | Knowledge of Google Cloud ML tools, programming skills in Python, TensorFlow | Statistical expertise, programming in Python/R, data analysis skills |
| Work Environment | Cloud platforms, AI/ML projects, collaboration with developers | Data analysis, reporting, model development, client communication |
| Industry Usage | Tech companies, AI startups, cloud service providers | Finance, healthcare, marketing, research organizations |
While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.
What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Connecticut?
For Freelance Google Machine Learning Engineer jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Freelance Google Machine Learning Engineer jobs in Connecticut look for?
The top searched job categories for Freelance Google Machine Learning Engineer jobs in Connecticut are:
What cities in Connecticut are hiring for Freelance Google Machine Learning Engineer jobs?
Cities in Connecticut with the most Freelance Google Machine Learning Engineer job openings:
Machine Learning Engineer
Shelton, CT • On-site
Sperry Rail, Inc.
• Trucking • 501 - 1,000 employees501 - 1,000 employees
Full-time
Posted 25 days ago
Sperry Rail Service rating
6.9
Based on 8 frontline employees who took The Breakroom Quiz
Job description
About Sperry:
Sperry Rail is on a mission-critical journey to revolutionize the Rail Flaw Detection industry. Through the continuous development of cutting-edge diagnostic technologies and AI-assisted analysis, we are transforming railway safety worldwide. Our global engineering teams work collaboratively to develop step-change technologies that define Sperry as the unparalleled market leader.
For nearly a century, we have repeatedly modernized and improved rail diagnostics through our relentless pursuit of improvement. Determined is an understatement. We are obsessed with advancing science and raising the bar on what's possible with our ever-improving suite of products and service offerings.
Emboldened through the shared values of honesty, accountability, passion, integrity, and teamwork, we are driven by the challenge and bridging concepts with fruition. Each technologist entering Sperry imprints themselves into our brand and further galvanizes a culture of innovation and advancement. Allow us to be clear, Thought Leaders are welcome!
We are agile and hungry and invite those with similar passions to join us in challenging the status quo and bringing new ideas to the market. Fast-paced, high-touch with a distinct sense of purpose. We offer more than a job; we offer an opportunity to be part of something different.
Role Summary
We are building a US data science team of three: a lead who owns risk analytics for our customers' track, a data scientist working on the quality of analyst decisions, and you. You are the engineer. What the other two build in notebooks, you turn into systems that run on a schedule, hold up under real data, and can be handed to someone else. That covers the full model lifecycle. Packaging and deployment, the pipelines that feed models, versioning of data and models together, monitoring for drift and degradation, retraining, and the plumbing that gets a result in front of the person who needs it. We are early enough that you get to choose most of this rather than inherit it. You will not be doing this on bare ground. A cloud engineering team across the US and UK looks after our AWS platform, networking, and security, and the UK engineering team runs the data platform and the inspection products. Your work sits on top of theirs, and getting that boundary right is part of the job. We hold years of ultrasonic, induction, and eddy current test data from non-stop inspection across North America. Volume is not the constraint here. Getting reliable, reproducible answers out of it is.
What We Expect From You
We expect an exceptional level of drive and ambition. You think beyond today's work to what the team and organization need next, champion bold ideas, and see them through. Your hunger is infectious - it inspires those around you to aim higher. You should be someone who puts the team first. You share credit openly, admit when you are wrong, and welcome feedback as an opportunity to grow. You are comfortable saying "I don't know" and asking for help when needed. This role requires a high degree of self-direction. You will manage complex work with minimal oversight, identify problems and solutions proactively, and may lead workstreams. You make well-reasoned technical decisions and escalate when there is genuine business or architectural impact. You should be able to quickly grasp complex problems that span multiple systems or domains. We expect you to design effective solutions for non-trivial requirements, identify root causes efficiently, and consider performance, scalability, and maintainability in your approach. You will be the person who insists that a result is reproducible. That is a temperament as much as a skill, and it is the main reason this seat exists as an engineering role rather than a third analyst.
Key Responsibilities
• Take models and analyses from prototype to production, and own them once they are there
• Build and maintain the data pipelines that feed models, working with large-scale rail inspection data including ultrasonic, electromagnetic, and operational sources
• Implement model and data versioning so that any result can be traced back to the code and data that produced it
• Monitor deployed models for drift, degradation, and data quality problems, and build the retraining paths that respond to them
• Build and maintain APIs and services that deliver model output to the people and systems that consume it
• Design and implement the compute and orchestration for training and inference workloads on AWS (S3, Lambda, Glue, Step Functions, SageMaker, or equivalents)
• Set the team's engineering standards: testing, code review, environments, CI/CD, and release practice
• Work with the cloud engineering team on the platform underneath, and with the UK data and platform teams on shared data sources
• Automate the manual steps between an idea and a running model, so the data scientists spend their time on method
• Write clean, tested, well-documented code following engineering best practices
• Participate in code reviews, sprint planning, and technical design discussions
• Document architecture decisions, runbooks, and operational procedures
Required Skills & Qualifications
• Strong proficiency in Python, including the scientific stack (NumPy, Pandas, Scikit-learn, or similar)
• Experience putting machine learning models or statistical analyses into production and keeping them running
• Experience building data pipelines and working with structured and unstructured data at scale
• Solid understanding of SQL and relational and non-relational databases
• Experience with AWS cloud services and cloud-native architecture
• Practical experience with containerization (Docker) and infrastructure-as-code
• Understanding of software engineering principles: testing, code quality, design patterns
• Familiarity with version control (Git), CI/CD pipelines, and agile development practices
• Strong problem-solving skills and ability to learn new technologies quickly
• Good communication skills - able to explain technical concepts to non-technical stakeholders
• A collaborative, team-first mindset aligned with our values of being Humble, Hungry, and Smart Qualifications and years of experience are indicative guidelines, not mandatory requirements. These criteria may be met through demonstrated competency or equivalent experience.
Desirable Skills
• Bachelor's degree in computer science, engineering, or a related technical field
• MLOps tooling: MLflow, SageMaker Pipelines, Kubeflow, DVC, Weights & Biases, or similar
• Workflow orchestration (Airflow, Dagster, Prefect, Step Functions)
• Observability and monitoring tooling (CloudWatch, Grafana, Datadog, or similar)
• Experience being the first engineer on a data science team
• Signal processing or work with sensor data
• Experience in rail testing, NDT, or sensor-based inspection industries (ultrasound, eddy current, electromagnetic, etc.)
Sperry Rail is on a mission-critical journey to revolutionize the Rail Flaw Detection industry. Through the continuous development of cutting-edge diagnostic technologies and AI-assisted analysis, we are transforming railway safety worldwide. Our global engineering teams work collaboratively to develop step-change technologies that define Sperry as the unparalleled market leader.
For nearly a century, we have repeatedly modernized and improved rail diagnostics through our relentless pursuit of improvement. Determined is an understatement. We are obsessed with advancing science and raising the bar on what's possible with our ever-improving suite of products and service offerings.
Emboldened through the shared values of honesty, accountability, passion, integrity, and teamwork, we are driven by the challenge and bridging concepts with fruition. Each technologist entering Sperry imprints themselves into our brand and further galvanizes a culture of innovation and advancement. Allow us to be clear, Thought Leaders are welcome!
We are agile and hungry and invite those with similar passions to join us in challenging the status quo and bringing new ideas to the market. Fast-paced, high-touch with a distinct sense of purpose. We offer more than a job; we offer an opportunity to be part of something different.
Role Summary
We are building a US data science team of three: a lead who owns risk analytics for our customers' track, a data scientist working on the quality of analyst decisions, and you. You are the engineer. What the other two build in notebooks, you turn into systems that run on a schedule, hold up under real data, and can be handed to someone else. That covers the full model lifecycle. Packaging and deployment, the pipelines that feed models, versioning of data and models together, monitoring for drift and degradation, retraining, and the plumbing that gets a result in front of the person who needs it. We are early enough that you get to choose most of this rather than inherit it. You will not be doing this on bare ground. A cloud engineering team across the US and UK looks after our AWS platform, networking, and security, and the UK engineering team runs the data platform and the inspection products. Your work sits on top of theirs, and getting that boundary right is part of the job. We hold years of ultrasonic, induction, and eddy current test data from non-stop inspection across North America. Volume is not the constraint here. Getting reliable, reproducible answers out of it is.
What We Expect From You
We expect an exceptional level of drive and ambition. You think beyond today's work to what the team and organization need next, champion bold ideas, and see them through. Your hunger is infectious - it inspires those around you to aim higher. You should be someone who puts the team first. You share credit openly, admit when you are wrong, and welcome feedback as an opportunity to grow. You are comfortable saying "I don't know" and asking for help when needed. This role requires a high degree of self-direction. You will manage complex work with minimal oversight, identify problems and solutions proactively, and may lead workstreams. You make well-reasoned technical decisions and escalate when there is genuine business or architectural impact. You should be able to quickly grasp complex problems that span multiple systems or domains. We expect you to design effective solutions for non-trivial requirements, identify root causes efficiently, and consider performance, scalability, and maintainability in your approach. You will be the person who insists that a result is reproducible. That is a temperament as much as a skill, and it is the main reason this seat exists as an engineering role rather than a third analyst.
Key Responsibilities
• Take models and analyses from prototype to production, and own them once they are there
• Build and maintain the data pipelines that feed models, working with large-scale rail inspection data including ultrasonic, electromagnetic, and operational sources
• Implement model and data versioning so that any result can be traced back to the code and data that produced it
• Monitor deployed models for drift, degradation, and data quality problems, and build the retraining paths that respond to them
• Build and maintain APIs and services that deliver model output to the people and systems that consume it
• Design and implement the compute and orchestration for training and inference workloads on AWS (S3, Lambda, Glue, Step Functions, SageMaker, or equivalents)
• Set the team's engineering standards: testing, code review, environments, CI/CD, and release practice
• Work with the cloud engineering team on the platform underneath, and with the UK data and platform teams on shared data sources
• Automate the manual steps between an idea and a running model, so the data scientists spend their time on method
• Write clean, tested, well-documented code following engineering best practices
• Participate in code reviews, sprint planning, and technical design discussions
• Document architecture decisions, runbooks, and operational procedures
Required Skills & Qualifications
• Strong proficiency in Python, including the scientific stack (NumPy, Pandas, Scikit-learn, or similar)
• Experience putting machine learning models or statistical analyses into production and keeping them running
• Experience building data pipelines and working with structured and unstructured data at scale
• Solid understanding of SQL and relational and non-relational databases
• Experience with AWS cloud services and cloud-native architecture
• Practical experience with containerization (Docker) and infrastructure-as-code
• Understanding of software engineering principles: testing, code quality, design patterns
• Familiarity with version control (Git), CI/CD pipelines, and agile development practices
• Strong problem-solving skills and ability to learn new technologies quickly
• Good communication skills - able to explain technical concepts to non-technical stakeholders
• A collaborative, team-first mindset aligned with our values of being Humble, Hungry, and Smart Qualifications and years of experience are indicative guidelines, not mandatory requirements. These criteria may be met through demonstrated competency or equivalent experience.
Desirable Skills
• Bachelor's degree in computer science, engineering, or a related technical field
• MLOps tooling: MLflow, SageMaker Pipelines, Kubeflow, DVC, Weights & Biases, or similar
• Workflow orchestration (Airflow, Dagster, Prefect, Step Functions)
• Observability and monitoring tooling (CloudWatch, Grafana, Datadog, or similar)
• Experience being the first engineer on a data science team
• Signal processing or work with sensor data
• Experience in rail testing, NDT, or sensor-based inspection industries (ultrasound, eddy current, electromagnetic, etc.)
What Sperry Rail Service employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Sperry Rail
Sourced by ZipRecruiter
Industry
Trucking
Company size
501 - 1,000 Employees
Headquarters location
Shelton, CT, US
Year founded
1928