As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users ...
Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users ...
Machine Learning Engineer
San Mateo, CA · On-site
$110K - $165K/yr
Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift : N/A Location : San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role ...
Machine Learning Engineer
San Mateo, CA · On-site
$110K - $165K/yr
Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift : N/A Location : San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role ...
The Role As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world ...
Quick apply
The Role As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world ...
Machine Learning Engineer
Long Beach, CA · On-site
They are seeking a Machine Learning Engineer to join their Applied Algorithms and Autonomy team, where the role involves designing and developing machine learning and AI capabilities to support ...
Machine Learning Engineer
Long Beach, CA · On-site
They are seeking a Machine Learning Engineer to join their Applied Algorithms and Autonomy team, where the role involves designing and developing machine learning and AI capabilities to support ...
Machine Learning Engineer
San Mateo, CA · On-site
$110K - $165K/yr
Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift : N/A Location : San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role ...
Machine Learning Engineer
San Mateo, CA · On-site
$110K - $165K/yr
Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift : N/A Location : San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role ...
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 ...
Machine Learning Engineer
San Francisco, CA · On-site +1
Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...
Machine Learning Engineer
San Francisco, CA · On-site +1
Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...
Machine Learning Engineer
San Francisco, CA · On-site
Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...
Machine Learning Engineer
San Francisco, CA · On-site
Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...
Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...
Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...
Machine Learning Engineer
San Francisco, CA · On-site
$225K - $300K/yr
Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...
Machine Learning Engineer
San Francisco, CA · On-site
$225K - $300K/yr
Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...
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 the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...
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 the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...
Machine Learning Engineer
Mountain View, CA · On-site
They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...
Machine Learning Engineer
Mountain View, CA · On-site
They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...
Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...
Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Quick apply
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Machine Learning Engineer
Cupertino, CA · On-site
Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...
Machine Learning Engineer
Cupertino, CA · On-site
Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...
Machine Learning Engineer
Chatsworth, CA · On-site
$160K - $190K/yr
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Machine Learning Engineer
Chatsworth, CA · On-site
$160K - $190K/yr
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Machine Learning Engineer
San Jose, CA · On-site
As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...
Machine Learning Engineer
San Jose, CA · On-site
As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...
We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...
We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...
Machine Learning Engineer
San Francisco, CA · On-site
$164K - $266K/yr
What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...
Machine Learning Engineer
San Francisco, CA · On-site
$164K - $266K/yr
What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...
Machine Learning Engineer Biotech information
What does a Machine Learning Engineer do in the biotech industry?
A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.
How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?
Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in Biotech, and why are they important?
To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.
What is the difference between Machine Learning Engineer Biotech vs Data Scientist Biotech?
| Aspect | Machine Learning Engineer Biotech | Data Scientist Biotech |
|---|---|---|
| Required Credentials | Bachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworks | Bachelor's or Master's in Data Science, Statistics, or related; strong analytical skills |
| Work Environment | Develops ML models, coding, deploying algorithms in biotech R&D | Analyzes biological data, interprets results, creates reports |
| Employer & Industry Usage | Biotech firms, pharma companies, research labs | Biotech companies, healthcare, research institutions |
While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.
What are the most commonly searched types of Machine Learning Engineer Biotech jobs in California? The most popular types of Machine Learning Engineer Biotech jobs in California are:
What are popular job titles related to Machine Learning Engineer Biotech jobs in California? For Machine Learning Engineer Biotech jobs in California, the most frequently searched job titles are:
- Freelance Machine Learning Data Annotation
- Internship Edge Ai Machine Learning
- Deep Learning Engineer
- Flexible Machine Learning Engineer Biotech
- Artificial Intelligence Programmer
- Contract Machine Learning Engineer Biotech
- Machine Learning Engineer Apprenticeship
- Remote Prototype Machinist
- Google Cloud Machine Learning Engineer
- Lead Machine Learning Engineer
What job categories do people searching Machine Learning Engineer Biotech jobs in California look for? The top searched job categories for Machine Learning Engineer Biotech jobs in California are:
What cities in California are hiring for Machine Learning Engineer Biotech jobs? Cities in California with the most Machine Learning Engineer Biotech job openings:
Other
Posted 18 days ago
Job description
Who are we?
RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
Key ResponsibilitiesSupport the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
Analyze the impact of integrating new data sources and features into our models.
Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
Document experiments, assumptions, and outcomes; maintain reproducibility
Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.
At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.
Experience with machine learning techniques such as regression, classification, and clustering.
Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
Strong grasp of probability, statistics, and data analysis principles.
Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
Familiarity with system programming languages including C++ and Rust is a plus.
Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.