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Machine Learning Engineer

onhires · Remote
RemoteFull-timeMachine LearningConstruction$145,000–$195,000/yr
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About the Machine Learning Engineer role

Machine Learning Engineer positions focus on delivering results in their domain. This page aggregates open Machine Learning Engineer roles and what employers typically expect.

We’re hiring on behalf of A1, a high‑talent team building the next generation of AI‑native productivity applications. Their mission is to replace repetitive digital work with AI that can reliably complete real tasks for everyday users. Rather than building another chatbot, A1 is creating long‑running AI workflows that manage conversations, coordinate actions, maintain context, and interact with external services — all with minimal user input. As a Machine Learning Engineer, you will own critical ML subsystems in production. This is a hands‑on, high‑impact role focused on depth and reliability at scale. WHAT YOU’LL DO - Build core ML systems powering a proactive, long‑horizon AI product. - Own the full lifecycle: data preparation, training, evaluation, inference, iteration. - Turn research ideas into production systems that run reliably. - Debug model failures and system issues using real production signals. - Ship quickly, measure outcomes, refine, and repeat. - Collaborate closely with research, product, and engineering teams. - Mentor and review work from other ML engineers. - Work under real production constraints: latency, cost, reliability, safety. TECH STACK - Python - PyTorch / JAX - GPU‑based training and inference systems IDEAL BACKGROUND - Experience building and shipping ML systems used by real users. - Strong understanding of how modern ML models behave — and misbehave — in production. - Ability to write production‑quality code and think in systems, not scripts. - Independent ownership: driving work across the finish line. - Fast learner, clear communicator, iterative mindset. EXPECTED OUTCOMES - ML models and systems consistently meet accuracy, latency, reliability, and efficiency targets. - Complex production issues are monitored, debugged, and resolved with minimal disruption. - Training, inference, and data pipelines are robust, scalable, and maintainable. - Measurable improvements in ML systems based on real‑world signals and user feedback. - Technical guidance and mentorship that raises the overall ML engineering standard. - Seamless integration of ML features into products that meet business goals. HOW A1 WORKS Our client A1 is a small, world‑class team with high talent density. They move quickly, make decisions collectively, and balance shipping high‑quality work with rapid learning. Structure, sound judgment, and the ability to execute independently are highly valued. INTERVIEW PROCESS - 3–4 interviews with technical team members. - Conducted virtually and/or onsite. - Transparent and efficient decision process. - Successful candidates will receive an offer to join a team building AI that delivers practical benefits to billions of users globally.

Salary estimate

$145,000 – $195,000/yr
Provided by the employer.

Skills for this role

PythonPytorchMachine Learning

Resume tips for Machine Learning Engineer applicants

Interview preparation

Prepare concrete STAR-format stories that show Machine Learning Engineer outcomes you drove.

Research the employer's product and recent news before the interview.

Be ready to explain how you'd approach a typical Machine Learning Engineer problem end to end.

Have thoughtful questions ready about the team, tools and success metrics.

About onhires

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