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Machine Learning Engineer Manager Jobs in California

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

... data management and accuracy. * In both theoretical development environments and specific product ... May substitute equivalent machine learning engineer experience in lieu of education. * Must have an ...

... Learning Engineer to develop and deploy lightweight machine learning models for edge AI ... managed IT services. Founded in 2017, the company is headquartered in Boulder, USA, with a team of ...

Partner with ML engineers, product managers, data scientists, and software engineers to align ML ... machine learning modeling or related fields * Experience with deep learning technologies for ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

Partner with ML engineers, product managers, data scientists, and software engineers to align ML ... machine learning modeling or related fields * Experience with deep learning technologies for ...

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing ... Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and ...

Showing results 21-40

Machine Learning Engineer Manager information

What is a machine learning engineer manager?

Machine Learning Engineer Managers are professionals who lead teams of machine learning engineers in designing, developing, and deploying machine learning models and systems. They combine strong technical expertise in machine learning with leadership and project management skills to guide teams, set priorities, and ensure projects align with organizational goals. In addition to overseeing technical work, they are responsible for mentoring team members, collaborating with other departments, and staying updated on the latest ML technologies and best practices.

What are the main challenges machine learning engineer managers face when leading teams?

Machine Learning Engineer Managers often navigate the dual challenge of aligning technical innovation with business goals while supporting team growth. They must balance hands-on technical guidance with project management, ensuring that machine learning models are both cutting-edge and production-ready. Additionally, fostering collaboration between data scientists, engineers, and stakeholders is crucial to keeping projects on track and team members motivated. Managing shifting priorities and keeping up with rapid advancements in AI technology are also common aspects of the role.

What are the key skills and qualifications needed to thrive as a machine learning engineer manager, and why are they important?

To thrive as a Machine Learning Engineer Manager, you need a strong background in computer science, machine learning algorithms, and leadership, often supported by an advanced degree and experience managing technical teams. Familiarity with tools like Python, TensorFlow, PyTorch, cloud platforms, and project management systems is essential, along with certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Excellent communication, strategic thinking, and mentorship abilities help foster team growth and drive project success. These skills are crucial for delivering impactful ML solutions, ensuring efficient team performance, and aligning technical work with organizational goals.

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

AspectMachine Learning Engineer ManagerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; often leadership experienceBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentLeads ML teams, manages projects, collaborates with engineeringAnalyzes data, builds models, reports insights, collaborates with business units
Employer & Industry UsageTech companies, AI firms, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis and modeling skills

The main difference is that a Machine Learning Engineer Manager oversees ML teams and projects, focusing on leadership and strategy, while a Data Scientist primarily analyzes data and builds models to extract insights. Both roles require strong technical skills, but the manager role adds leadership responsibilities.

Are machine learning engineer managers still in demand?

Machine Learning Engineer Managers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They require strong technical skills, leadership abilities, and knowledge of tools like Python, TensorFlow, and cloud platforms, making their roles critical in developing and overseeing AI projects.

What are the most commonly searched types of Machine Learning Engineer jobs in California?

The most popular types of Machine Learning Engineer jobs in California are:

What cities in California are hiring for Machine Learning Engineer Manager jobs?

Cities in California with the most Machine Learning Engineer Manager job openings:

Infographic showing various Machine Learning Engineer Manager job openings in California as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Member of Technical Staff | Machine Learning

San Francisco, CA • On-site

$200K - $280K/yr

Full-time

Medical, Dental, Vision

Re-posted 29 days ago


Key responsibilities

  • Develop models, signals, and evaluation frameworks that support investment decision-making.

  • Design and run experiments to evaluate and improve model and agent performance.

  • Build reproducible workflows for feature generation, training, validation, and evaluation.


Job description

About Poesis
Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal.
About the Role
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.
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.