Iterate on Kensho’s ML processes to develop tools, services, and frameworks that make every stage of the ML workflow robust, auditable, and usable.
Work closely with ML engineers to understand their unique processes, identify pain points, and form effective solutions.
Empower engineers with the stable tooling necessary to rapidly experiment and actualize their research into demonstrable prototypes and mature products
Provide resources and training for ML teams on best practices, enabling them to efficiently productionize their work to be leveraged by high-value products and services
Evaluate, select and champion open source and third-party solutions, driving their adoption across teams and integrating into Kensho’s existing platform ecosystem
Ship scalable, efficient, and automated processes for model fine-tuning and reinforcement learning and for the evaluation of LLMs/Agents
Improve LLM and Agentic observability to help monitor agentic applications in production, detecting performance, decay and drift issues
Stay at the frontier by actively tracking emerging tools and frameworks, promote best practices and strengthen the technical expertise of the team with your unique skill set

Requirements

2+ years of experience in ML infra, ML Ops, ML Engineering or some similar skillset
Experience managing distributed systems with Kubernetes.
Cloud Platform (AWS) understanding. We utilize tools like EKS and managed ML services like Bedrock and SageMaker
Python proficiency (we are a python shop mostly)
Familiarity with distributed computing frameworks and workflow orchestration (ie. Ray, Airflow)
Familiarity with software engineering best practices in an ML context
Some basic understanding of ML concepts, LLMs and agents
Ability to debug distributed systems across infrastructure, networking and application layers
Excellent communication skills to drive adoption of new tools and best practices across multiple teams
Someone who’s very curious, driven, low-ego and eager to learn across a range of engineering disciplines, while being part of a fantastic team.

Benefits

Medical, Dental, and Vision insurance 100% company paid premiums
Unlimited Paid Time Off
26 weeks of 100% paid Parental Leave (paternity and maternity)
401(k) plan with 6% employer matching
Generous company matching on donations to non-profit charities
Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences
Plentiful snacks, drinks, and regularly catered lunches
Dog-friendly office (CAM office)
Bike sharing program memberships
Compassion leave and elder care leave
Mentoring and additional learning opportunities
Opportunity to expand professional network and participate in conferences and events

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningML Opsdistributed systemsKubernetesAWSPythonRayAirflowmodel fine-tuningreinforcement learning

Soft Skills

communicationcuriositydrivenlow-egoeager to learn