Sr. ML Engineer (MLOps)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. ML Engineer (MLOps) based in the United States.

This is an opportunity for a senior machine learning engineer to build the infrastructure and services that bring ML and generative AI products into production.
You will play a hands-on role in developing reliable tooling, platforms, APIs, and services that support the full ML and AI development lifecycle.
The position combines software engineering, MLOps, cloud infrastructure, model deployment, evaluation, and production operations.
You will work closely with data scientists, analysts, product leaders, and domain experts to solve complex problems with meaningful real-world impact.
As a senior technical contributor, you will take ownership of major initiatives, influence engineering decisions, and mentor other team members.
The environment values thoughtful engineering, rapid learning, cross-functional collaboration, and pragmatic decisions that balance quality with delivery.
This fully remote role is ideal for someone who enjoys building systems from the ground up and turning advanced AI capabilities into dependable production products.

Accountabilities

• Build and maintain the tooling, platforms, and backend services that power machine learning and generative AI solutions in production.
• Develop services supporting model training, inference, deployment, monitoring, and other stages of the ML/AI lifecycle.
• Build and maintain model evaluation metrics, testing frameworks, and supporting infrastructure to assess the quality and reliability of ML and generative AI systems.
• Develop APIs and production services that expose machine learning and AI capabilities to applications and users.
• Deploy and manage applications supporting different components of the AI/ML software development lifecycle.
• Design scalable, maintainable systems using modern software engineering and MLOps practices.
• Develop high-quality production code, primarily in Python, while contributing to architecture, implementation, testing, and operational excellence.
• Collaborate with data scientists, data analysts, product managers, and other technical and domain specialists to translate complex requirements into effective technical solutions.
• Take ownership of cross-functional initiatives from initial design through deployment and ongoing improvement.
• Provide technical guidance, mentorship, and engineering best practices to other team members.
• Help evaluate and introduce new technologies that can improve ML development, deployment, testing, and operational workflows.
• Contribute to the development of retrieval-augmented generation solutions and vector-based AI infrastructure where appropriate.
• Work with sensitive and business-critical data while maintaining strong standards for security, reliability, privacy, and system quality.
• Balance engineering quality, scalability, and maintainability with business priorities and delivery timelines.

Requirements

• 6+ years of experience deploying machine learning or AI solutions in production environments.
• Strong Python programming skills and a demonstrated ability to write clean, maintainable, production-quality code.
• Experience designing and developing RESTful APIs and production backend services.
• Experience defining and working with Protobuf messages and service interfaces.
• Hands-on experience with Docker and deploying applications to Kubernetes.
• Experience working with relational databases and low-latency data stores.
• Experience using Celery or comparable technologies for distributed or asynchronous task processing.
• Strong understanding of machine learning and AI production workflows, including deployment, inference, evaluation, testing, and operational support.
• Demonstrated ability to learn new technologies quickly and apply them effectively to complex engineering challenges.
• Strong interest in building ML- and AI-powered products and production systems from the ground up.
• Excellent communication skills and the ability to build consensus across technical and non-technical stakeholders.
• Strong organizational and prioritization skills, with the ability to turn complex problems into clear, actionable priorities.
• Ability to take ownership, work independently, and drive cross-functional initiatives to completion.
• Thoughtful approach to balancing engineering quality, technical debt, business priorities, and deadlines in a fast-paced environment.
• Experience building retrieval-augmented generation (RAG) solutions is preferred.
• Experience setting up and maintaining vector databases is preferred.
• Production software development experience with Java or Kotlin is a plus.
• Experience building and operating solutions on AWS or other cloud infrastructure is preferred.
• Experience working with highly sensitive data, particularly within healthcare or similarly regulated environments, is beneficial.

Benefits

• Salary: Annual base salary range of $143,000–$197,000 , with placement based on skills, qualifications, experience, location, and other job-related factors.
• Additional compensation: Eligibility for discretionary bonuses and equity through restricted stock units.
• Healthcare: Comprehensive medical, dental, and vision coverage, along with FSA/HSA options.
• Insurance: Life and disability insurance coverage.
• Mental health support: Access to coaching and therapy services as part of the employee wellness offering.
• Retirement: 401(k) plan with up to a 3% employer match .
• Paid time off: Competitive vacation, sick leave, and company holiday policies.
• Parental support: Paid parental leave.
• Technology support: Monthly technology allowance.
• Well-being: Wellness perks, community activities, employee celebrations, and additional engagement programs.
• Work environment: Fully remote position with opportunities to collaborate across multidisciplinary teams.
• Professional growth: Hands-on exposure to advanced ML, generative AI, MLOps, cloud infrastructure, and production-scale engineering challenges.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.