BJAK Logo

BJAK

Senior Machine Learning Engineer

Reposted 11 Days Ago
Remote or Hybrid
Hiring Remotely in United States
Senior level
Remote or Hybrid
Hiring Remotely in United States
Senior level
The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.
The summary above was generated by AI
About the Role

A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.

As a Senior Member of Technical Staff, Machine Learning, you are an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale.

This is a hands-on, high-impact role focused on depth.

Focus
  • Build core ML systems that power a proactive, long-horizon AI product.

  • Own work end-to-end: data preparation, training, evaluation, inference, and iteration.

  • Turn research ideas into working systems that run reliably in production.

  • Debug model failures and system issues using real production signals.

  • Iterate quickly: ship, measure outcomes, refine, and repeat.

  • Collaborate closely with research, product, and engineering to deliver real user impact.

  • Mentor and review work from other ML engineers through example and technical judgment.

  • Work under real production constraints: latency, cost, reliability, and safety

Tech Stack
  • Python

  • PyTorch / JAX

  • GPU-based training and inference systems

Ideal Experience
  • You have built and shipped ML systems used by real users.

  • You understand how modern ML models behave — and misbehave — in production.

  • You write strong, production-quality code and think in systems, not scripts.

  • You take ownership, work independently, and push work across the finish line.

  • You learn fast, communicate clearly, and improve through iteration.

Outcomes
  • ML models and systems in production 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 over time.

  • Drives measurable improvements in ML systems based on real-world signals and user feedback.

  • Provides mentorship and technical guidance to peers, raising the overall ML engineering standard.

  • Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals.

How We Work

The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

Interview process

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

Top Skills

Jax
Python
PyTorch

Similar Jobs

8 Hours Ago
Remote or Hybrid
170K-240K Annually
Senior level
170K-240K Annually
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
As a Senior Machine Learning Engineer, you'll design scalable AI/ML infrastructure, optimize model training performance, and collaborate with teams to implement advanced AI solutions.
Top Skills: AWSAzureGCPPythonPyTorchTensorFlow
9 Days Ago
In-Office or Remote
70K-87K Annually
Senior level
70K-87K Annually
Senior level
Fintech • Machine Learning • Payments • Social Impact • Software • Financial Services
The Senior Machine Learning Engineer will architect the ML infrastructure, productionize models, maintain data platforms, and ensure system health, collaborating closely with data scientists and data engineers.
Top Skills: AWSCdkCloudFormationDatabricksDockerDynamoDBKafkaKubernetesPythonPyTorchSagemakerScikit-LearnSnowflakeTensorFlowTerraform
24 Days Ago
Remote or Hybrid
United States
119K-201K Annually
Senior level
119K-201K Annually
Senior level
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.
Top Skills: AirflowAWSCloudbeesDbtFeastGoJenkinsKafkaPythonPyTorchQlikScikit-LearnShell/BashSnowflakeSQLTableauTensorFlow

What you need to know about the Boston Tech Scene

Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.

Key Facts About Boston Tech

  • Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
  • Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
  • Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
  • Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account