Machine Learning Engineer

Spectrix Analytical Services, LLC; United States; Remote; USD 66,000 - 80,000; Full time

Benefits offered by this job

Life insurance

Disability insurance

Health, dental, and vision insurance (

College loan assistance

Employer matched retirement savings

Job summary

Spectrix Analytical Services, LLC is seeking a Machine Learning Platform and Agentic AI Engineer for a contract remote role focused on building compute, MLOps, and tooling that supports protein therapeutic design.

You will develop production Python services, deploy Kubernetes across AWS regions, and implement Helm charts, CI/CD, and data pipelines. Collaboration with scientists and engineers, plus documentation and hands-on adoption support, are essential to success.

Qualifications

• Bachelor’s degree with 7–10 years of relevant experience, or Master’s degree with 5+ years of relevant experience.
• Strong Python development skills with production-grade tooling or pipelines.
• Working knowledge of Kubernetes, Helm, and container deployments in production.
• Experience developing, deploying, or optimizing machine learning pipelines in production.
• Familiarity with infrastructure-as-code and CI/CD practices.
• AWS experience, including multi-region or multi-account deployments.
• Data warehousing and ELT pattern experience, with Snowflake preferred.
• Experience working on a small team (3–10 engineers) with end-to-end ownership and shipping without dedicated QA, SRE, or release functions.
• Routine use of agentic coding harnesses such as Claude Code, OpenCode, Codex, or equivalent.

Responsibilities

• Develop and maintain production Python services, pipelines, and CLI tooling.
• Build and maintain Helm charts, container images, and deployment infrastructure as part of the daily workflow.
• Deploy and operate workloads on Kubernetes across multiple AWS regions and accounts.
• Instrument pipelines and models so performance, cost, and benchmark results are measurable.
• Collaborate with scientists and engineering leads to decide what to build.
• Support adoption through documentation and hands-on help.

Skills

Python development

Kubernetes knowledge

CI/CD practices

Remote collaboration

Strong documentation

Effective communication

Self-directed

Education

Bachelor's degree

Master's degree

Tools

Python

Kubernetes

Helm

CI/CD

AWS

Snowflake

Claude Code

OpenCode

Codex

S3

Job description

Contract remote role for a Machine Learning Platform and Agentic AI Engineer building compute, MLOps, and tooling that supports protein therapeutic design.

Responsibilities

• Develop and maintain production Python services, pipelines, and CLI tooling.
• Build and maintain Helm charts, container images, and deployment infrastructure as part of the daily workflow.
• Deploy and operate workloads on Kubernetes across multiple AWS regions and AWS accounts.
• Instrument pipelines and models so performance, cost, and benchmark results are measurable.
• Collaborate with scientists and engineering leads to decide what to build.
• Support adoption through documentation and hands‑on help.

Requirements

• Bachelor’s degree with 7–10 years of relevant experience, or Master’s degree with 5+ years of relevant experience.
• Strong Python development skills with experience building production‑grade tooling or pipelines.
• Working knowledge of Kubernetes, Helm, and container‑based deployments.
• Experience developing, deploying, or optimizing machine learning pipelines in production.
• Familiarity with infrastructure-as-code and CI/CD practices.
• AWS experience, including multi‑region or multi‑account deployments.
• Data warehousing and ELT pattern experience, with Snowflake preferred.
• Experience working on a small team (approximately 3–10 engineers) with end‑to‑end ownership, self‑directed prioritization within goals, and shipping without dedicated QA, SRE, or release functions.
• Routine use of agentic coding harnesses such as Claude Code, OpenCode, Codex, or equivalent, including judgment on where they help and where they do not.
• Willingness to learn computational biology and protein science domains.
• Effective communicator able to work independently in a remote environment and collaborate with engineers and scientists.

Key Work Areas

• Extend the Kubernetes orchestration platform and the workflows running on it, including migrating existing application backends onto it.
• Make the platform region‑agnostic so compute can be scheduled in new AWS regions and accounts via configuration rather than code changes.
• Build model registration, versioning, and the serving path so model outputs are available to scientific applications and downstream reporting.
• Integrate model output with the data layer rather than keeping it as per‑project artifacts.
• Build automated benchmarking and retraining for computational tools, LLM models, and agent skills used in de novo design.
• Include GPU‑backed benchmarking of larger models, test‑set and dataset tracking, and persistent benchmark result history over time.
• Incorporate agentic AI into existing scientific applications by defining tools and skills, creating evaluation harnesses, and adding the plumbing that lets agents call internal services safely.
• Build S3‑to‑Snowflake data pulls and automated registration of de novo design results, including monitoring and backfill behavior without manual intervention.
• Reduce runtime and cost of existing production pipelines through profiling, GPU utilization, batching, scheduling, and container image work.

Technologies

• Python
• Kubernetes
• Helm
• Containerized deployments
• AWS
• S3
• Snowflake
• CI/CD
• Infrastructure‑as‑code
• Claude Code
• OpenCode
• Codex

Compensation & Employment

• Location: Remote
• Job type: Contract
• Pay: USD 48–58 per hour

Benefits

• Automatic benefits of life insurance and short and long term disability insurance
• Optional health, dental, and vision insurance for full time employees
• College loan assistance
• Employer matched retirement savings plan

Company Overview

• Spectrix Analytical Services, LLC provides on‑site analytical chemistry services with reliable, high‑quality results since 1999.
• Team of experienced scientists supports R&D across various industries by generating precise analytical data and maintaining sophisticated instrumentation directly at clients’ laboratories.