Senior Machine Learning Engineer

Description

The machine learning developer builds applications whose core behavior comes from models rather than hand-written rules, and owns them from design through production operation.

You will work on the engine behind the company's optimization products, the algorithms and pipelines that solve complex scheduling and resource-allocation problems and deliver fast, dependable results to customers.

AI now plays two roles in this work: applying machine learning to optimization problems, and using AI agents in the build process. The role needs both an engineer who can design an efficient algorithm from scratch and one who can define a problem tightly enough to direct an agent to build part of it, then check the output is correct. You are accountable for the correctness, performance and robustness of what ships, whether a person or an agent wrote it.

Responsibilities

• Design, build and run production optimization applications at scale, covering API design, data ingestion, multiprocessing, observability, advanced algorithm development, performance benchmarking and automated testing.
• Design and maintain the automated evaluation system that lets the team test model behavior and ship features with confidence.
• Turn requirements into testable specifications with clear scope, constraints and acceptance criteria, split the work into tasks sized for AI agents, and review their output for correctness and maintainability.
• Help shape how the team's AI harness is used to get value from coding agents.
• Manage deployments, monitor service availability, set up alerts and fix customer issues before customers notice them.
• Work directly with customers when needed, learn their business needs and product fit, help them reach value sooner, and feed what you learn back into the product roadmap.
• Work with product managers, designers, conversation designers and engineers to set success criteria, agree on tradeoffs and explain capability and risk in plain terms.

Requirements

• 5+ years of related experience and a bachelor's degree in computer science, software engineering or a related technical field.
• Strong grounding in object-oriented programming, data structures, algorithms, system design, concurrency, parallelism, APIs, data modeling and testing.
• Python is strongly preferred. Java, JavaScript, Kubernetes or GraphQL experience is a bonus.
• Hands-on experience with some of: Python, MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQL.
• Able to work directly with customers when information is incomplete and deadlines are fixed. You know when a quick local fix fits and when to wait for the lasting solution, and you can explain capability, limits and risk to non-engineers.
• Proven record building reliable, resilient systems for mission-critical use.
• Strong critical thinking and a record of bringing AI into engineering processes, the software development lifecycle, workflows or decisions.
• Knowledge of operations research, vehicle routing, mathematical optimization or field service management is a plus but not required. Advanced degrees or certifications, especially in operations research, are a bonus.

Conditions

Work persona (flexible, remote or required in office) is assigned by the nature of the work and work location. To confirm eligibility, the company may measure the distance between your main residence and the nearest office using a third-party service.