Senior ML Engineer (AI Research/ Portability)

Responsibilities

Our talent team is representing a confidential AI research organization seeking a Senior ML Engineer to advance applied research in AI portability. You will design and build research prototypes and production-grade systems at the intersection of language models, agent runtimes, and provider infrastructure.

Your responsibilities will include:

• Designing, implementing, training, and evaluating model routing systems that select appropriate models or reasoning profiles for each conversational turn based on quality, cost, latency, and reliability objectives
• Developing portable provider and protocol abstractions that preserve authentication, telemetry, cache signals, context state, and execution provenance across heterogeneous inference environments
• Defining versioned schemas and execution contracts for models, agents, workspaces, skills, actions, tools, memories, and agent trajectories
• Building systems that discover, package, adapt, and validate agent skills across coding agents, editor integrations, and other execution harnesses
• Researching user-owned memory architectures with scoped identity, trajectory checkpoints, terminal outcomes, retrieval quality, and reviewable context compaction
• Creating benchmark suites and evaluation protocols for quality, cost, latency, reliability, safety, and portability across model and provider changes
• Designing held-out, out-of-domain, and change-impact evaluations that test robustness when models, providers, skills, or harness versions are added or removed
• Investigating distillation techniques, self-improving harnesses, multi-agent training, agent factories, and automated skill generation
• Writing robust research software, APIs, integration layers, and test infrastructure that enable rapid yet reproducible experimentation
• Collaborating across research and engineering teams to translate promising ideas into secure, reversible, and reliable production systems
• Communicating results through technical reports, demonstrations, open-source releases, benchmarks, and research publications

What We're Looking For

Required qualifications:

• Profound understanding of machine learning, large language models, or statistical decision-making systems
• Deep expertise in at least one relevant area: model routing, recommender systems, agent systems, retrieval and memory architectures, model evaluation, distributed systems, or protocol and API design
• Experience building and evaluating modern language-model or agentic systems, including tool use and multi-turn workflows
• Experience designing, executing, and analyzing machine learning experiments with appropriate statistical rigor
• Ability to formulate meaningful research questions, design experiments that test clear hypotheses, and draw defensible conclusions
• Understanding of evaluation leakage, held-out testing, out-of-domain generalization, uncertainty estimation, and reproducibility
• Strong software-engineering and algorithm-design skills with excellent Python proficiency and ability to work across production systems
• Experience with APIs, data schemas, distributed services, testing, observability, code review, and CI/CD workflows
• Ability to reason about security, privacy, provenance, permissions, failure modes, and user control in agent systems
• Experience implementing research ideas and iterating quickly across modeling, data, systems, and evaluation dimensions
• Strong communication and technical leadership abilities, including cross-disciplinary collaboration and clear documentation of findings

Nice to have:

• Experience with model routers, cascades, mixture-of-experts systems, recommenders, or cost-aware inference
• Experience integrating multiple model providers or inference stacks, including various API formats and local inference systems
• Familiarity with agent harnesses, coding agents, editor integrations, function calling, tool execution, or agent-to-agent protocols
• Experience with retrieval systems, vector search, knowledge graphs, temporal data, memory architectures, or context management
• Experience with benchmark suites for coding, reasoning, factuality, instruction following, tool use, or multi-turn agent workflows
• Experience with teacher-student distillation, reinforcement learning, preference learning, reward modeling, or automated skill generation
• Proficiency in TypeScript, Go, Rust, or another systems language in addition to Python
• Experience with secure authentication, sandboxing, privacy-preserving telemetry, provenance tracking, or policy-enforced execution
• Experience building distributed data-processing, evaluation, model-training, or inference systems
• PhD in Computer Science, Machine Learning, Artificial Intelligence, or related technical field, or equivalent practical experience
• Track record of impactful publications, open-source contributions, or deployed AI systems
• Record of building and delivering products or research prototypes in dynamic, startup-like environments
• Passion for making advanced AI systems composable, inspectable, user-controlled, and resilient to changing models and platforms

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your background and schedule an initial screening conversation. We work closely with our client to identify candidates whose expertise aligns with their research priorities in AI portability, model routing, agent interoperability, and memory systems.

After our screening, we will submit qualified candidates directly to our client for their interview process. Please apply exclusively through Get A Job.ai and do not contact the client organization directly, as doing so may disqualify your application.

This is a remote position with flexibility to work from various locations. Applicants must be authorized to work in the country in which they apply.

Pay

Compensation details will be discussed during the screening process and are competitive for senior-level ML engineering roles in applied AI research.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and provide equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, or any other protected characteristic.