About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...
About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...
Machine Learning Engineer
$200K - $400K/yr
About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...
Machine Learning Engineer
$200K - $400K/yr
About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...
The Machine Learning Engineer will be responsible for scaling models, building training infrastructure, and ensuring reproducibility across large-scale biological datasets while collaborating with ...
The Machine Learning Engineer will be responsible for scaling models, building training infrastructure, and ensuring reproducibility across large-scale biological datasets while collaborating with ...
Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...
Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...
As a Machine Learning Engineer, you will shape the technical direction of the company by automating the ML life-cycle and engaging directly with customers while contributing to the architectural ...
As a Machine Learning Engineer, you will shape the technical direction of the company by automating the ML life-cycle and engaging directly with customers while contributing to the architectural ...
This role We're looking for a machine learning engineers who can work on large-scale image and video models training experiments. What you'll do * Train foundation diffusion models for image and ...
This role We're looking for a machine learning engineers who can work on large-scale image and video models training experiments. What you'll do * Train foundation diffusion models for image and ...
Machine Learning Operations Engineer (MLOps)
Fremont, CA · On-site
$50 - $100/hr
The successful candidate will work directly with Process Engineering, Product Engineering, Test Engineering, Manufacturing, MES, and IT teams to build data pipelines, develop machine learning models ...
Quick apply
Machine Learning Operations Engineer (MLOps)
Fremont, CA · On-site
$50 - $100/hr
The successful candidate will work directly with Process Engineering, Product Engineering, Test Engineering, Manufacturing, MES, and IT teams to build data pipelines, develop machine learning models ...
Machine Learning Engineer
San Francisco, CA · On-site
$200K - $400K/yr
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Machine Learning Engineer
San Francisco, CA · On-site
$200K - $400K/yr
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Machine Learning Engineer
San Francisco, CA · On-site +1
$140K - $190K/yr
As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won't just train models in isolation; you will build end-to-end pipelines ...
Machine Learning Engineer
San Francisco, CA · On-site +1
$140K - $190K/yr
As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won't just train models in isolation; you will build end-to-end pipelines ...
They are seeking a Machine Learning Engineer to train and deploy critical models for their core product, focusing on interpreting unstructured data and improving model performance. Responsibilities ...
They are seeking a Machine Learning Engineer to train and deploy critical models for their core product, focusing on interpreting unstructured data and improving model performance. Responsibilities ...
The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This is a hands-on engineering role focused on making models faster, more efficient, and more reliable ...
The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This is a hands-on engineering role focused on making models faster, more efficient, and more reliable ...
Machine Learning Engineer
San Francisco, CA · On-site
$210K - $240K/yr
Machine Learning Engineer You'll build the ML behind Firecrawl - the models and the systems that serve them. That starts with search: training and shipping the ranking and relevance models for one of ...
Machine Learning Engineer
San Francisco, CA · On-site
$210K - $240K/yr
Machine Learning Engineer You'll build the ML behind Firecrawl - the models and the systems that serve them. That starts with search: training and shipping the ranking and relevance models for one of ...
Conduit builds autonomous factories through a single data abstraction layer across every machine ... Translate customer needs into clean engineering briefs for the SF team. Build relationships with ...
New
Conduit builds autonomous factories through a single data abstraction layer across every machine ... Translate customer needs into clean engineering briefs for the SF team. Build relationships with ...
New
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Menlo Park, CA · On-site
$271K/yr
Meta is seeking a Machine Learning Engineer to join our integrity engineering team. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale ...
Machine Learning Engineer (Technical Leadership)
Menlo Park, CA · On-site
$271K/yr
Meta is seeking a Machine Learning Engineer to join our integrity engineering team. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale ...
Lead Machine Learning Engineer
San Francisco, CA · On-site +1
$120K - $159K/yr
Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...
Lead Machine Learning Engineer
San Francisco, CA · On-site +1
$120K - $159K/yr
Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...
Machine Learning Engineer
San Francisco, CA · On-site
$250K - $385K/yr
The Opportunity We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you ...
Machine Learning Engineer
San Francisco, CA · On-site
$250K - $385K/yr
The Opportunity We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you ...
Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure * Mentor and elevate other engineers through technical leadership ...
Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure * Mentor and elevate other engineers through technical leadership ...
Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure * Mentor and elevate other engineers through technical leadership ...
Quick apply
Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure * Mentor and elevate other engineers through technical leadership ...
Machine Learning Manager
San Francisco, CA · On-site
$180K - $250K/yr
The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...
Machine Learning Manager
San Francisco, CA · On-site
$180K - $250K/yr
The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...
Machine Learning Manager
$180K - $250K/yr
The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...
Machine Learning Manager
$180K - $250K/yr
The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving ... Machine Learning Manager In order to execute our vision, we're constantly growing our machine ...
Machine Learning Petroleum Engineer information
See Berkeley, CA salary details
$38.6K - $56.6K
1% of jobs
$56.6K - $74.6K
1% of jobs
$74.6K - $92.7K
5% of jobs
$92.7K - $110.7K
6% of jobs
$125.6K is the 25th percentile. Wages below this are outliers.
$110.7K - $128.7K
14% of jobs
$128.7K - $146.8K
14% of jobs
The median wage is $155.8K / yr.
$146.8K - $164.8K
18% of jobs
$164.8K - $182.8K
14% of jobs
$186.5K is the 75th percentile. Wages above this are outliers.
$182.8K - $200.9K
12% of jobs
$200.9K - $218.9K
11% of jobs
$218.9K - $236.9K
5% of jobs
$38.6K
$157.7K
$236.9K
How much do machine learning petroleum engineer jobs pay per year?
As of Sep 2, 2026, the average yearly pay for machine learning petroleum engineer 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 a machine learning petroleum engineer?
A Machine Learning Petroleum Engineer is a specialist who combines expertise in petroleum engineering with machine learning and data science techniques. They use advanced algorithms and data analytics to optimize oil and gas exploration, drilling, production, and reservoir management. Their work helps improve decision-making, reduce operational costs, and increase efficiency by analyzing large datasets from various sources such as sensors, seismic data, and production logs. These professionals often work closely with geoscientists, data engineers, and other stakeholders in the energy sector.
What are the key skills and qualifications needed to thrive as a machine learning petroleum engineer?
To thrive as a Machine Learning Petroleum Engineer, you need a strong background in petroleum engineering, programming (such as Python or R), and applied machine learning, usually supported by a relevant engineering degree. Familiarity with data analysis platforms, machine learning frameworks (like TensorFlow or Scikit-learn), and petroleum industry software (such as Petrel or Eclipse) is essential. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for integrating technical insights with business goals. These competencies enable the effective application of data-driven solutions to optimize exploration, production, and operational efficiency in the energy sector.
How does a machine learning petroleum engineer typically collaborate with geoscientists and drilling teams to optimize oil and gas production?
A Machine Learning Petroleum Engineer works closely with geoscientists and drilling teams by integrating data-driven models into exploration and production workflows. They analyze geological, seismic, and operational data to develop predictive algorithms that identify optimal drilling locations, forecast reservoir performance, and improve recovery rates. Regular collaboration involves translating complex data insights into actionable recommendations that guide drilling strategies and inform real-time decisions, ensuring all teams are aligned to maximize efficiency and safety. This multidisciplinary approach fosters continuous learning and innovation across teams.
What is the difference between Machine Learning Petroleum Engineer vs Reservoir Engineer?
| Aspect | Machine Learning Petroleum Engineer | Reservoir Engineer |
|---|---|---|
| Required Credentials | Bachelor's/Master's in Petroleum Engineering, Data Science, or related fields; knowledge of machine learning | Bachelor's/Master's in Petroleum Engineering or Geosciences; strong understanding of reservoir simulation |
| Work Environment | Data analysis, modeling, software development in oil & gas companies | Reservoir modeling, field development planning in oil & gas operations |
| Industry Usage | Applying machine learning to optimize extraction, predict reservoir behavior | Estimating reservoir properties, managing production strategies |
The Machine Learning Petroleum Engineer focuses on integrating data science and machine learning techniques to optimize oil extraction processes, while the Reservoir Engineer specializes in modeling and managing subsurface reservoirs to maximize recovery. Both roles are vital in the oil & gas industry but differ in their core skills and daily tasks.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in Berkeley, CA?
For Machine Learning Petroleum Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What cities near Berkeley, CA are hiring for Machine Learning Petroleum Engineer jobs?
Cities near Berkeley, CA with the most Machine Learning Petroleum Engineer job openings:
Full-time
Medical, Dental, Vision, Retirement, PTO
Posted 27 days ago
Job description
About Plenful
Plenful is on a mission to transform healthcare operations from the inside out. Fresh off our $50M Series B and backed by Notable Capital, Bessemer Venture Partners, TQ Ventures, Susa/Kivu Ventures, and other leading investors, we're building the category-defining AI workflow automation platform that healthcare teams rely on to operate smarter, faster, and more efficiently. Our technology empowers healthcare operators across hospital and health systems, pharmacies and payors to eliminate manual work, reduce administrative burden, and improve compliance, all while unlocking critical revenue to fund programs for their in-need patient populations.
Built by healthcare operators for healthcare operators, Plenful is driven by a deep understanding of the challenges facing today's care teams. We're passionate about equipping healthcare workers with world-class tools that deliver real, measurable impact, and we're proud to serve 90+ leading health systems across the country. If you're excited to help shape the future of healthcare, we'd love to meet you. Apply now to join our growing team.
About the Role
We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to-end lifecycle - from experimentation to production deployment to ongoing model performance.
You'll partner closely with software engineers, product managers, and data teams to build models and intelligent services that automate healthcare workflows, improve operational efficiency, and create great user experiences. This is an engineering-focused role, and your work will directly impact customers.
You'll thrive here if you enjoy solving hard problems with practical engineering solutions, take ownership from idea through production, and balance experimentation with delivering reliable software. We're a fast-moving startup where priorities evolve quickly - you should be energized by that, not worn down by it.
What You'll Do
Bonus points if you:
Technologies you'll likely work with: Python, PyTorch, TensorFlow, Scikit-learn, SQL, PostgreSQL, Docker, Kubernetes, AWS, GitHub Actions, REST APIs, vector databases, and LLM APIs (OpenAI, Anthropic, etc.)
Why You'll Love Working Here
Plenful is on a mission to transform healthcare operations from the inside out. Fresh off our $50M Series B and backed by Notable Capital, Bessemer Venture Partners, TQ Ventures, Susa/Kivu Ventures, and other leading investors, we're building the category-defining AI workflow automation platform that healthcare teams rely on to operate smarter, faster, and more efficiently. Our technology empowers healthcare operators across hospital and health systems, pharmacies and payors to eliminate manual work, reduce administrative burden, and improve compliance, all while unlocking critical revenue to fund programs for their in-need patient populations.
Built by healthcare operators for healthcare operators, Plenful is driven by a deep understanding of the challenges facing today's care teams. We're passionate about equipping healthcare workers with world-class tools that deliver real, measurable impact, and we're proud to serve 90+ leading health systems across the country. If you're excited to help shape the future of healthcare, we'd love to meet you. Apply now to join our growing team.
About the Role
We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to-end lifecycle - from experimentation to production deployment to ongoing model performance.
You'll partner closely with software engineers, product managers, and data teams to build models and intelligent services that automate healthcare workflows, improve operational efficiency, and create great user experiences. This is an engineering-focused role, and your work will directly impact customers.
You'll thrive here if you enjoy solving hard problems with practical engineering solutions, take ownership from idea through production, and balance experimentation with delivering reliable software. We're a fast-moving startup where priorities evolve quickly - you should be energized by that, not worn down by it.
What You'll Do
- Design, build, and deploy machine learning models into production
- Develop scalable ML pipelines for training, evaluation, monitoring, and inference
- Build intelligent services using modern NLP, LLM, classification, recommendation, and prediction techniques where appropriate
- Collaborate with Product and Engineering to translate customer problems into ML solutions
- Improve model performance through experimentation, feature engineering, and evaluation
- Work with structured and unstructured datasets to develop production-ready features
- Implement monitoring, observability, and retraining strategies to maintain model quality
- Optimize model latency, scalability, and infrastructure costs
- Contribute to architecture discussions and engineering best practices
- Stay current with advancements in machine learning and AI, and bring practical innovations into our platform
- You have 5+ years of professional software engineering or machine learning engineering experience
- You have a Bachelor's degree in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field (or equivalent practical experience)
- You have strong programming experience in Python
- You've built and deployed machine learning models into production environments
- You have a solid understanding of supervised and unsupervised learning techniques
- You're familiar with modern ML infrastructure - classical MLOps (MLflow, Weights & Biases, Airflow) and LLMOps (LangFuse/LangSmith for tracing, Ragas/Braintrust for evaluation, vLLM/BentoML for serving, and a vector database such as Pinecone, Weaviate, or Qdrant for RAG pipelines)
- You've built data pipelines using SQL and distributed data processing tools
- You're familiar with cloud platforms such as AWS, GCP, or Azure
- You've deployed containerized applications using Docker and Kubernetes
- You have a strong grasp of software engineering fundamentals - testing, version control, and CI/CD
- You communicate well and collaborate easily across technical and non-technical teams
Bonus points if you:
- Have worked with Large Language Models (LLMs), retrieval-augmented generation (RAG), embeddings, or agentic AI systems
- Have fine-tuned foundation models or worked with prompt engineering techniques
- Are familiar with ML infrastructure tools such as MLflow, Weights & Biases, Airflow, Kubeflow, or SageMaker
- Have experience with vector databases and semantic search technologies
- Have healthcare, pharmacy, or health tech experience
- Have worked in a startup or other fast-paced environment
Technologies you'll likely work with: Python, PyTorch, TensorFlow, Scikit-learn, SQL, PostgreSQL, Docker, Kubernetes, AWS, GitHub Actions, REST APIs, vector databases, and LLM APIs (OpenAI, Anthropic, etc.)
Why You'll Love Working Here
- Mission-Driven, World-Class Team - Join an exceptional group of professionals aligned around a meaningful mission and committed to making an impact
- Opportunities for Growth - Strengthen your expertise through collaboration with experienced, high-performing leaders across the organization
- Flexible Hybrid Work Environment - We're remote-first, with meaningful office presence in San Francisco and New York. R&D roles follow a hybrid model, with two days per week in our San Francisco office
- Healthcare Coverage - Full medical, dental, and vision insurance for you and participation for your family
- 401(k) with Company Match - Plenful matches 50% of your first 3% contributed
- Equity - Every full-time employee shares in our success
- Unlimited PTO - Take the time you need, when you need it
- Daily Lunch Stipend - $100/week to cover your midday meals
- Wellness Stipend - $100/month to support your health and well-being
- Commuter Benefits - $100/month for SF and NYC-based employees
- Parental Leave - Paid leave to support growing families
About Plenful
Sourced by ZipRecruiter
Industry
Health care and social assistance
Company size
11 - 50 Employees
Headquarters location
San Francisco, CA, US
Year founded
2020