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Ml Inference Jobs in Massachusetts (NOW HIRING)

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Optimize models for real-time or near-real-time inference in embedded or product environments ... Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Optimize models for real-time or near-real-time inference in embedded or product environments ... Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow ...

Abbott

Staff AI/ML Engineer

Westford, MA · On-site

$99K - $198K/yr

Optimize models for real-time or near-real-time inference in embedded or product environments ... Strong programming skills in Python and experience with ML frameworks such as PyTorch, TensorFlow ...

Pragmatike

Principal AI/ML Engineer

Boston, MA · On-site

... inference, and evaluation pipelines for structured and unstructured data • Own model performance ... ML codebases primarily in Python • Monitor, debug, and improve live production models • ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

... and inference across GPU clusters • Collaborate with research scientists to translate experimental ML approaches into production-ready code • Design and execute ML experiments with clear ...

WHOOP

Technical Lead, ML Operations

Boston, MA · On-site

... ML platform. Responsibilities : • Own the technical vision, roadmap, and delivery for a core ... time inference systems. • Demonstrated ability to balance hands-on technical work with team ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

... and inference across GPU clusters • Collaborate with research scientists to translate experimental ML approaches into production-ready code • Design and execute ML experiments with clear ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

... and inference across GPU clusters • Collaborate with research scientists to translate experimental ML approaches into production-ready code • Design and execute ML experiments with clear ...

Manifold Bio

AI/ML Research Engineer

Boston, MA · On-site

... and inference across GPU clusters • Collaborate with research scientists to translate experimental ML approaches into production-ready code • Design and execute ML experiments with clear ...

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Ml Inference information

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?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch 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 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.

What are the key skills and qualifications needed to thrive in ML inference?

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.

Is ML inference a high paying job?

ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.
What are popular job titles related to Ml Inference jobs in Massachusetts? For Ml Inference jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Massachusetts look for? The top searched job categories for Ml Inference jobs in Massachusetts are:
What cities in Massachusetts are hiring for Ml Inference jobs? Cities in Massachusetts with the most Ml Inference job openings:
Ml Inference jobs near you

Senior Lead AI Engineer (FM Hosting, LLM Inference)

Capital One

Cambridge, MA

Full-time

Re-posted 11 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

91st of 171 rated banks

Job description

Senior Lead AI Engineer (FM Hosting, LLM Inference)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

  • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

  • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies

  • At least 6 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

  • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

  • Experience designing, developing, integrating, delivering, and supporting complex AI systems

  • Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders

  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers


Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer


McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer


New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer


San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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