Senior AI/ML Engineer – GenAI, ML Platform & MLOps

Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite empowers imagination with intelligence. And that it will be such Fractalites that will continue to build the company for the next 100 years.Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Location: RemoteNote: This Position Is Not Eligible for Immigration Sponsorship at This Time.Role overviewHands-on engineer to develop, deploy, and operate production AI/ML solutions, with a focus on large language models (LLMs), retrieval-augmented generation (RAG), and agents.

The role combines applied AI engineering with backend service design, scalable model serving, and MLOps to deliver reliable, observable, and secure AI services.The engineer will work with the customer AI team, applied scientists, architects, and platform teams to translate business requirements and research findings into production solutions, improve model quality, and own the engineering lifecycle from implementation through operational support.Key responsibilitiesApplied AI and GenAI engineering. Design and implement ML and GenAI solutions for real-time and batch use cases. Develop and evaluate RAG pipelines and agent workflows; improve model and application quality through experimentation, model adaptation, and collaboration on fine-tuning where required.Backend and API services. Build maintainable inference APIs and backend services with clear contracts, input validation, authentication, authorization, versioning, and consistent error handling. Integrate AI services with enterprise applications and data platforms.Request lifecycle and traceability. Track requests from acceptance to completion using request and correlation IDs, durable job status, structured logs, and distributed tracing. Maintain traceability to model, prompt, configuration, and retrieval versions with appropriate protection of sensitive data.Asynchronous processing. Implement queues, workers, and orchestration for long-running requests. Handle retries, idempotency, timeouts, cancellation, failures, and result retrieval through polling or callbacks, as appropriate.Scalable model serving. Design for concurrency, availability, and throughput. Apply load balancing, autoscaling, batching, caching, and resource optimization; manage backpressure and downstream limits while balancing latency, quality, and cost.MLOps and release engineering. Automate build, test, deployment, and environment promotion through CI/CD. Manage experiment tracking, model registries, artifact and configuration versioning, reproducible deployments, release validation, and rollback.Quality and production operations. Implement unit, integration, load, and model evaluation tests. Monitor availability, latency, errors, resource usage, inference cost, and model quality or drift where applicable. Investigate incidents and maintain runbooks.Responsible AI and collaboration. Implement evaluation, safety, privacy, and audit controls with governance teams. Define technical success metrics, communicate results and trade-offs to stakeholders, contribute to the innovation agenda, and coach less experienced engineers.Required qualificationsProven experience delivering and supporting AI/ML services in production, with hands-on ownership across backend development, model serving, and deployment automation.Strong Python programming and software engineering skills, including modular design, automated testing, source control, code review, and troubleshooting.Experience designing backend APIs and distributed services, including asynchronous processing, queues, workers, durable request state, retries, and idempotency.Practical experience with LLM applications, RAG, embeddings, retrieval, or agent workflows, including evaluation of output quality and reliability.Hands-on experience with containers, orchestration, CI/CD, infrastructure as code, and at least one major cloud platform; ability to implement secure, repeatable deployments.Experience with model or artifact versioning, experiment tracking, deployment validation, monitoring, logging, and distributed tracing.Sound understanding of ML fundamentals, deep learning concepts, statistics, and experimental methods sufficient to assess model behavior and engineering trade-offs.Ability to translate ambiguous requirements into technical solutions, work independently, explain complex issues to technical and business stakeholders, and mentor colleagues.Preferred qualificationsExperience fine-tuning LLMs, parameter-efficient adaptation, or improving pretrained model performance through systematic experimentation.Advanced knowledge of deep learning, optimization, applied mathematics, and statistics; experience translating research into practical AI solutions.Experience optimizing GPU inference, distributed workloads, or large-scale data processing, including performance and cost tuning.Experience with Responsible AI evaluations, guardrails, adversarial testing, and AI solutions in healthcare or other regulated environments.Pay:The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $130,000 - $150,000. In addition, you may be eligible for a discretionary bonus for the current performance period.

Benefits

As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take time needed for either sick time or vacation.Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.