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Remote Full Stack Machine Learning Engineer Jobs in Massachusetts

... machine. At Steer, you aren't just a contributor; you are the architect of a platform aiming for ... Learning Stipend & WFH Equipment: Everything you need for a world-class home office. * Innovative ...

Software Engineer, Full Stack

Boston, MA ยท On-site +1

$115K - $125K/yr

... remote We are looking for a collaborative Full Stack Software Engineer and team player to join one ... As a Software Engineer, you are known for thinking on your feet, learning quickly, and owning a ...

Sr. Distinguished Engineer

Cambridge, MA ยท On-site +1

$114.20K - $156.80K/yr

As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering ... At least 4 years of experience with the full ML development lifecycle using modern technology in a ...

This is a remote role. Tech stack * Backend: Scala, GCP services * Frontend: React + TypeScript ... By leveraging massive amounts of data and advanced machine learning algorithms, Hopper combines its ...

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Remote Full Stack Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as a Remote Full Stack Machine Learning Engineer, and why are they important?

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote Full Stack Machine Learning Engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

What is a Remote Full Stack Machine Learning Engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What is the difference between Remote Full Stack Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Massachusetts? The most popular types of Full Stack Machine Learning Engineer jobs in Massachusetts are:
What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in Massachusetts? For Remote Full Stack Machine Learning Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in Massachusetts look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in Massachusetts are:

Principal Machine Learning Engineer, Distributed vLLM Inference

Redhat

Boston, MA โ€ข On-site, Remote

$189.60K - $312.73K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago


Job description

Job Summary
At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise. Red Hat Inference team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading developers, maintainers of the vLLM and LLM-D projects, and inventors of state-of-the-art techniques for model quantization and sparsification, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments.

As a Principal Machine Learning Engineer focused on distributed vLLM infrastructure in the llm-dproject, you will collaborate with our team to tackle the most pressing challenges in scalable inference systems and Kubernetes-native deployments. Your work with distributed systems and cloud infrastructure will directly impact enterprise AI deployments. You would be joining the core team behind2025's most popular open source project on GitHub.! If you want to solve challenging technical problems in distributed systems and cloud-native infrastructure the open-source way, this is the role for you.

Join us in shaping the future of AI!

Red Hat will not be providing visa sponsorship for this position. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.

What you will do

  • Develop and maintain distributed inference infrastructure leveraging Kubernetes APIs, operators, and the Gateway Inference Extension API for scalable LLM deployments.

  • Create system components in Go and/or Rust to integrate with the vLLM project and manage distributed inference workloads.

  • Design and implement KV cache-aware routing and scoring algorithms to optimize memory utilization and request distribution in large-scale inference deployments.

  • Enhance the resource utilization, fault tolerance, and stability of the inference stack.

  • Contribute to the design, development, and testing of various inference optimization algorithms.

  • Actively participate in technical design discussions and propose innovative solutions to complex challenges.

  • Provide timely and constructive code reviews.

  • Mentor and guide fellow engineers, fostering a culture of continuous learning and innovation.

What you will bring

  • Strong proficiency in Python, GoLang and at least one of the following: Rust, or C++.

  • Experience with cloud-native Kubernetes service mesh technologies/stacks such as Istio, Cilium, Envoy (WASM filters), and CNI.

  • A solid understanding of Layer 7 networking, HTTP/2, gRPC, and the fundamentals of API gateways and reverse proxies.

  • Working knowledge of high-performance networking protocols and technologies including UCX, RoCE, InfiniBand, and RDMA is a plus.

  • Excellent communication skills, capable of interacting effectively with both technical and non-technical team members.

  • A Bachelor's or Master's degree in computer science, computer engineering, or a related field.

Following is considered a plus

  • Experience with the Kubernetes ecosystem, including core concepts, custom APIs, operators, and the Gateway API inference extension for GenAI workloads.

  • Experience with GPU performance benchmarking and profiling tools like NVIDIA Nsight or distributed tracing libraries/techniques like OpenTelemetry.

  • Ph.D. in an ML-related domain is a significant advantage

#LI-MD2

#AI-HIRING

#vllm-1

The salary range for this position is $189,600.00 - $312,730.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

About Red Hat

Red Hat is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits
Comprehensive medical, dental, and vision coverage
Flexible Spending Account - healthcare and dependent care
Health Savings Account - high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability, paid family medical leave, and paid military leave
Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States.

Inclusion at Red Hat
Red Hat's culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.


Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application-assistance@redhat.com. General inquiries, such as those regarding the status of a job application, will not receive a reply.