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Senior Machine Learning Researcher Jobs (NOW HIRING)

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site

$147.40K - $194.30K/yr

The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL ...

MSCI

Machine Learning Researcher

San Francisco, CA

$144K - $187K/yr

Conduct research using machine learning methodologies that integrate financial theory with deep learning and reinforcement learning * Design and develop models that convert AI-extracted signals from ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147.40K - $194.30K/yr

The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

MSCI is establishing a Machine Learning Center of Excellence within the Research & Development team to develop machine learning models that power investment tools for institutional clients. We are ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

IMC

Machine Learning Researcher

Chicago, IL · On-site

$250K - $300K/yr

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

On our Machine Learning team, you'll build the deep learning models that power our trading ... At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and ...

Kiddom

Machine Learning Researcher

New York, NY · On-site

$180K - $280K/yr

As a Machine Learning Researcher , you will play a pivotal role in pushing the boundaries of what's possible with AI in education. Your work will assist teachers by personalizing their teaching ...

DraftKings, Inc.

Senior Machine Learning Engineer

New York, NY · On-site

$114.30K - $157K/yr

You'll turn cutting-edge machine learning research into scalable, production-ready systems that ... What you'll do as a Senior Machine Learning Engineer * Design and refine scalable pipelines for ...

Kiddom

Machine Learning Researcher

San Francisco, CA · On-site

$180K - $280K/yr

As a Machine Learning Researcher , you will play a pivotal role in pushing the boundaries of what's possible with AI in education. Your work will assist teachers by personalizing their teaching ...

DraftKings

Senior Machine Learning Engineer

Boston, MA

$113.50K - $155.90K/yr

You'll turn cutting-edge machine learning research into scalable, production-ready systems that ... What you'll do as a Senior Machine Learning Engineer * Design and refine scalable pipelines for ...

Kiddom

Machine Learning Researcher

New York, NY · On-site

$180K - $280K/yr

As a Machine Learning Researcher , you will play a pivotal role in pushing the boundaries of what's possible with AI in education. Your work will assist teachers by personalizing their teaching ...

DraftKings

Senior Machine Learning Engineer

New York, NY · On-site

$114.30K - $157K/yr

You'll turn cutting-edge machine learning research into scalable, production-ready systems that ... What you'll do as a Senior Machine Learning Engineer * Design and refine scalable pipelines for ...

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Senior Machine Learning Researcher information

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$28.5K

$76.6K

$137.5K

How much do senior machine learning researcher jobs pay per year?

As of May 29, 2026, the average yearly pay for senior machine learning researcher in the United States is $76,607.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Researcher, and why are they important?

To thrive as a Senior Machine Learning Researcher, you need advanced knowledge in machine learning algorithms, statistical analysis, programming (typically in Python), and a relevant advanced degree such as a PhD or Master's in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, as well as familiarity with cloud computing platforms and research publication, is often required. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and present complex ideas clearly. These skills and qualities are essential for driving innovation, developing robust models, and translating research into practical, impactful solutions.

What opportunities for collaboration typically exist for Senior Machine Learning Researchers within a company?

Senior Machine Learning Researchers frequently collaborate with cross-functional teams, including data engineers, software developers, and domain experts. This collaboration ensures that research insights are effectively translated into scalable solutions and integrated into products or services. Researchers often participate in brainstorming sessions, code reviews, and joint publications, fostering a culture of innovation and shared knowledge. These interactions not only drive the success of projects but also provide valuable learning experiences and networking opportunities.

What does a Senior Machine Learning Researcher do?

A Senior Machine Learning Researcher leads the development and application of advanced machine learning models to solve complex problems. They are responsible for designing experiments, analyzing large datasets, publishing research findings, and collaborating with engineering teams to implement solutions. Additionally, they mentor junior researchers, stay updated with the latest advancements in AI, and often contribute to setting the research agenda for their organization.

What is the difference between Senior Machine Learning Researcher vs Data Scientist?

AspectSenior Machine Learning ResearcherData Scientist
CredentialsAdvanced degrees in CS, ML, or related fieldsDegree in CS, statistics, or related fields; certifications optional
Work EnvironmentResearch labs, R&D teams, academiaBusiness analytics, product teams, startups
Industry UsageResearch-focused roles in tech, academia, R&DData analysis, business insights, product development
Search & Comparison IntentUnderstanding research vs applied roles in MLExploring data analysis careers and skills

While both roles involve working with data and machine learning, a Senior Machine Learning Researcher primarily focuses on developing new algorithms and advancing ML theory in research settings. In contrast, a Data Scientist applies existing models to analyze data, generate insights, and support business decisions. The roles differ mainly in their focus—research innovation versus practical application—though they share overlapping skills and credentials.

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Senior Machine Learning Researcher jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Freenome

Brisbane, CA • On-site

$147.40K - $194.30K/yr

Full-time

Posted 13 days ago

Job description

About this opportunity:
At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment.
The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimizing hardware utilization for efficient training, and performing model optimizations. As part of an interdisciplinary R&D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission of reducing cancer mortality via accessible early detection.
The role reports to the Director of Machine Learning Science. This can be a hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.
What you'll do:
  • Implement and refine DL pipelines on distributed computing platforms enhancing the speed and efficiency of DL operations including model training, data handling, model management, and inference.
  • Collaborate closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines you create are perfectly aligned with scientific goals and operational needs.
  • Continuously monitor, evaluate, and optimize DL model training pipelines for performance and scalability.
  • Stay up to date with the latest advancements in AI, ML, and related technologies, and quickly learn and adapt new tools and frameworks, if necessary.
  • Develop and maintain robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.
  • Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation pipelines.
  • Act as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.

Must haves:
  • MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.
  • 5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.
  • Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.
  • Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.
  • In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.
  • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.
  • Understanding of containerization technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.
  • Proven track record of developing and optimizing workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.
  • Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).
  • Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.
  • Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.
  • Excellent ability to work effectively with cross-functional teams and communicate across disciplines.

Nice to haves:
  • Experience working with large-scale genomics or biological datasets.
  • Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.
  • Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).
  • Experience with infrastructure-as-code and configuration management.
  • Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.
  • Strong track record of contributions to relevant DL projects, e.g. on github.

Benefits and additional information:
The US target range of our base salary for new hires is $161,925 - $227,325 You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company's sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.
Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Applicants have rights under Federal Employment Laws.
  • Family & Medical Leave Act (FMLA)
  • Equal Employment Opportunity (EEO)
  • Employee Polygraph Protection Act (EPPA)

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