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Remote Machine Learning Postdoc Jobs in San Jose, CA

6sense

Sr. Machine Learning Engineer

San Francisco, CA · Remote

$200K - $260K/yr

The Opportunity We're hiring a Senior Machine Learning Engineer to join our AI team, reporting ... remote Notice of Collection and Use of Personal Information for California Residents: California ...

EvenUp

Staff Machine Learning Engineer

San Francisco, CA · Remote

$212K - $301K/yr

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

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Remote Machine Learning Postdoc information

What is a remote machine learning postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

What are the key skills and qualifications needed to thrive as a remote machine learning postdoc?

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.

What are the most commonly searched types of Machine Learning Postdoc jobs in San Jose, CA?

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For Remote Machine Learning Postdoc jobs in San Jose, CA, the most frequently searched job titles are:

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Remote Machine Learning Postdoc jobs near you

Sr. Machine Learning Engineer

6sense

San Francisco, CA • Remote

$200K - $260K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 18 days ago

Key responsibilities

  • Own machine learning problems end to end, including data exploration, modeling, deployment, monitoring, and iteration in production.

  • Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.

  • Partner with Product and Go-to-Market teams to turn ambiguous business problems into shipped AI capabilities.

Job description

About 6sense

6sense is Intelligence for Agentic GTM. We turn every signal - yours and ours - into intelligence that every team, tool, and AI agent can act on and trust. Every day, the 6sense Signalverse captures one trillion signals to power AI that pinpoints who's ready to buy, how to engage them, and when to act. 6sense was named a Leader in The Forrester Wave: Revenue Marketing Platforms for B2B, Q1 2026.

The Opportunity

We're hiring a Senior Machine Learning Engineer to join our AI team, reporting directly to the Head of AI.

Signals tell you what happened. Our job is to explain why - and that is the problem you will work on. You will build the intelligence that turns a trillion daily signals into cited, explainable answers about why an account matters, why now, and who is deciding. Your models power products customers use every day, including RevvyAI, our conversational GTM intelligence product, and reach their stack through our APIs and MCP server.

This is a build-and-ship role, not a research role. You will own problems end to end, work directly with Product and Go-to-Market, and see your work reach customers. You'll join a team distributed across the US and India, at a company where AI is the product rather than a feature.

What You'll Do
  • Own machine learning problems end to end - from data exploration and modeling through deployment, monitoring, and iteration in production.
  • Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.
  • Develop ranking, recommendation, prediction, and optimization models that are explainable rather than black-box.
  • Partner with Product and Go-to-Market to turn ambiguous business problems into shipped capabilities.
  • Improve the performance, scalability, and reliability of production ML systems, and help shape AI platform architecture.
  • Explain your work clearly to technical and non-technical audiences, and engage with customers when needed.
  • Mentor engineers and raise the bar for engineering excellence.
What We're Looking ForRequired
  • 8+ years of industry experience building and deploying machine learning systems in production, with clear end-to-end ownership.
  • Strong foundation in machine learning and applied statistics, with hands-on depth in NLP, transformers, embeddings, and retrieval-based systems.
  • Practical experience with modern GenAI tooling such as LangGraph, LangChain, or Amazon Bedrock.
  • Strong Python skills and experience building distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent).
  • Solid grasp of feature engineering, model evaluation, and MLOps practices.
  • A product mindset - you want to build AI products customers use, and you measure yourself on customer impact.
  • Excellent communication: you can explain complex technical work clearly, tell the story of what you've built and why, and hold your own with product and business partners.
  • Comfort with ambiguity and the judgment to drive execution independently.
Nice to Have
  • Experience with RAG architectures, vector databases, and prompt engineering.
  • Hands-on work with PyTorch or TensorFlow.
  • Background in B2B SaaS, enterprise AI products, or forward-deployed engineering - especially where you worked directly with complex customer data and delivered quickly.

Base Salary Range: $200,349.50 - $260,912.60. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense's total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense's board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote

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