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Manager Remote Machine Learning Engineer Jobs in California

Otter.ai

Machine Learning Engineer

Mountain View, CA · On-site +1

$196K - $221K/yr

As a Machine Learning Engineer, you'll bring your strong software engineering mindset to machine learning in order to scale and optimize our ML systems-creating and transforming innovative research ...

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

YO AI Labs

Machine Learning Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Hiring Manager review. Compensation Compensation is output-based , with payment provided per task ...

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Manager Remote Machine Learning Engineer information

What is a manager remote machine learning engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

How does a manager remote machine learning engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.

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

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

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

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

Can a manager remote machine learning engineer work remotely?

Yes, a manager remote machine learning engineer can work remotely, as many companies offer remote positions for this role. Success in remote work often depends on strong communication skills, familiarity with collaboration tools, and the ability to manage projects independently.

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

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

What are popular job titles related to Manager Remote Machine Learning Engineer jobs in California?

For Manager Remote Machine Learning Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Manager Remote Machine Learning Engineer jobs in California look for?

The top searched job categories for Manager Remote Machine Learning Engineer jobs in California are:

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

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

Manager Remote Machine Learning Engineer jobs near you

Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home

San Francisco, CA • On-site, Remote

Ginas Tech Jobs
See more jobs at Ginas Tech Jobsexternal

Full-time

Medical, Dental, Vision, PTO

Re-posted 2 days ago

Job description

Company Description
Job Description
Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home
As the Staff Machine Learning Engineer, you own the execution layer of intelligence. You translate research direction into reliable, scalable, production-grade Machine Learning (ML) systems. This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints. This position is 100% Remote.
Staff Machine Learning Engineer Responsibilities:
- Own end-to-end Machine Learning (ML) system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- Design and maintain data systems for high-quality synthetic and real-world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate Machine Learning (ML) systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety
Staff Machine Learning Engineer Outcomes
- Research and models reliably translate into production-ready solutions with clear performance and quality targets.
- Machine Learning (ML) pipelines, training loops, and inference systems are stable, efficient, and maintainable.
- Production issues are detected, debugged, and resolved quickly, minimizing user impact.
- Team members are supported, aligned, and able to deliver high-impact Machine Learning (ML) work with minimal friction.
- Iterations on models and systems are measurable, safe, and improve user experience over time.
Qualifications
Staff Machine Learning Engineer Qualifications:
- Experience building or shipping real Machine Learning (ML) systems used by people, not just demos.
- Artificial Intelligence (AI) experience required.
- Experience working with large models and understanding their failure modes.
- Experience writing strong, production-grade code.
- You are self-directed, pragmatic, and take full ownership of outcomes.
- Experience communicating clearly and collaborate well in small, high-trust teams.
- Tech Stack: GPU-based training and inference system, JAX, Python, and PyTorch.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, Staff Machine Learning Engineer, Data Pipelines, DPO, GPU, JAX, LoRA, Machine Learning Engineer, ML, Machine Learning, Python, PyTorch, QLoRA, SFT, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Additional Information
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