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Machine Learning Engineer Hybrid Jobs in Berkeley, CA

Poesis Machine Learning Engineer At Poesis, machine learning and artificial intelligence open the ... Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this ... Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Designation Hybrid: Employee divides their time between in-office and remote work. Access to an ...

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and ... We follow a flexible hybrid model that translates to more than half your time on-site in our San ...

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model ... D. (preferred) or M.S. in Machine Learning, Computer Science, Electrical Engineering, Applied ...

Machine Learning Engineer Location: Fremont, CA Duration: 12+ Months Tesla/ $65 About the Role Our direct client is seeking a highly skilled Machine Learning Engineer to join their Software Machine ...

Machine Learning Engineer Fremont, California Gotion Inc. is based in Silicon Valley, CA, currently ... Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model ...

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios ...

Machine Learning Engineer We're looking for a Machine Learning Engineer to build and deploy production-grade AI systems. In this role, you'll take models from research to real-world applications ...

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

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Machine Learning Engineer Hybrid information

See Berkeley, CA salary details

$38.6K

$157.7K

$236.9K

How much do machine learning engineer hybrid jobs pay per year?

As of Jun 14, 2026, the average yearly pay for machine learning engineer hybrid in Berkeley, CA is $157,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $189,800.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Hybrid vs Data Scientist?

AspectMachine Learning Engineer HybridData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, deploys ML models; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works across departments
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Machine Learning Engineer Hybrid focuses on developing and deploying ML models within engineering environments, often requiring coding and deployment skills. Data Scientists analyze data, build models, and interpret results, often in research or strategic roles. While both roles require strong analytical skills and knowledge of ML, the Engineer Hybrid emphasizes deployment and integration, whereas Data Scientists focus on data analysis and insights.

What are popular job titles related to Machine Learning Engineer Hybrid jobs in Berkeley, CA? For Machine Learning Engineer Hybrid jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Hybrid jobs in Berkeley, CA look for? The top searched job categories for Machine Learning Engineer Hybrid jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Machine Learning Engineer Hybrid jobs? Cities near Berkeley, CA with the most Machine Learning Engineer Hybrid job openings:

Machine Learning Engineer

Poesis LLC

Menlo Park, CA

Other

Medical, Dental, Vision

Posted 25 days ago


Job description

Poesis Machine Learning Engineer

At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power investment decision-making across the platform. You'll work across the full machine learning lifecycle, from experimentation and model and agent development to deployment and iteration, with significant ownership over both research and production outcomes. This is a unique opportunity to help build a new approach to investing powered by AI.

Responsibilities
  • Rapidly implement and iterate on machine learning models, signals and research ideas
  • Design and run experiments to evaluate and improve model and agent performance and investment impact
  • Build reproducible workflows for feature generation, training, validation and evaluation
  • Work with large-scale financial, fundamental and alternative datasets to identify predictive signals and improve model performance
Required Competencies
  • 5+ years experience as a Machine Learning Engineer, or related role
  • Prior experience at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or similar
  • Strong Python and SQL skills, with experience working with large-scale datasets
  • Experience developing, evaluating and deploying machine learning models in production environments
  • Success building reproducible research workflows and experimentation frameworks
  • Familiarity with modern AI systems, including LLMs, evaluation frameworks, and agent workflows
  • Skill leveraging Claude Code, Codex, or other coding agents
  • BS/MS/PhD in Computer Science or a related field, or equivalent practical experience
Preferred Competencies
  • Experience developing ML and AI systems using financial, fundamental, alternative, or time-series datasets
  • Familiarity with quantitative investing, portfolio construction, or risk management
  • Experience with PyTorch or TensorFlow, and AI workflows for parsing financial documents (filings, transcripts)
Location

Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.

Benefits

We offer excellent medical, dental, and vision coverage, alongside a strong benefits package that includes catered lunches in our Menlo Park office, commuter benefits, and more. Current legal authorization to work in the US required; continuing work visa sponsorship available for full-time employees.

Working at Poesis

As an early team member, you'll help shape not just the product, but how the company operates. Your decisions will have lasting impact across the business. You'll build from first principles, with no legacy systems, or entrenched processes slowing you down. Our team is made up of people from elite companies and universities who are low ego, collaborative, and excited to build together.