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Principal Scientist Machine Learning Jobs (NOW HIRING)

Meta

Research Scientist, Machine Learning

Sunnyvale, CA · On-site

$122K - $181K/yr

Meta is seeking a Research Scientist to join our Core Machine Learning Research team, where we advance the foundational AI and ML technologies that power Meta's family of products at scale. In this ...

ISEE

Research Scientist - Machine Learning

... Science, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Control Engineering, Machine Learning, Statistics, or a related field - Passionate about self-driving vehicles and real ...

ISEE

Research Scientist - Machine Learning

... Science, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Control Engineering, Machine Learning, Statistics, or a related field - Passionate about self-driving vehicles and real ...

Team Velocity Marketing

$160K - $190K/yr

Senior Data Scientist - Machine Learning & AI Senior Data Scientist - Machine Learning & AI Remote | Full-Time | $160,000-$190,000 Team Velocity is seeking a Senior Data Scientist to develop and ...

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How much do principal scientist machine learning jobs pay per year?

As of Sep 11, 2026, the average yearly pay for principal scientist machine learning in the United States is $144,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,500.00 and $169,000.00 per year, depending on experience, location, and employer.

What does a principal scientist in machine learning do?

A Principal Scientist in Machine Learning leads advanced research and development projects focused on creating and improving machine learning models. They design experiments, analyze complex datasets, and develop algorithms to solve challenging problems in fields like artificial intelligence, data science, or computational biology. In addition to hands-on work, they often mentor junior team members, set research directions, and collaborate with cross-functional teams to integrate ML solutions into products or services. Their role is pivotal in driving innovation and ensuring that machine learning initiatives align with organizational goals.

What are the key skills and qualifications needed to thrive as a principal scientist in machine learning?

To thrive as a Principal Scientist in Machine Learning, you need advanced expertise in machine learning algorithms, statistical modeling, and a PhD or equivalent experience in computer science, mathematics, or a related field. Proficiency with programming languages like Python or R, deep learning frameworks (e.g., TensorFlow, PyTorch), and experience with cloud platforms are typically required. Strong leadership, communication, and problem-solving skills help drive cross-functional teams and innovative research. These skills are crucial for leading impactful ML projects, mentoring teams, and advancing organizational goals through cutting-edge solutions.

How does a principal scientist in machine learning typically collaborate with cross-functional teams on large-scale projects?

As a Principal Scientist in Machine Learning, you will frequently work alongside data engineers, product managers, domain experts, and software developers to ensure that ML models are both technically robust and aligned with business objectives. This role often involves leading technical discussions, setting research directions, and mentoring junior scientists. You may also be responsible for translating complex research outcomes into actionable insights for non-technical stakeholders, ensuring smooth integration of ML solutions into products or services. Effective communication and a collaborative mindset are essential, as these projects often require balancing technical innovation with practical constraints.

What cities are hiring for Principal Scientist Machine Learning jobs?

Cities with the most Principal Scientist Machine Learning job openings:

What states have the most Principal Scientist Machine Learning jobs?

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What are popular job titles related to Principal Scientist Machine Learning jobs?

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Infographic showing various Principal Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $144,009 per year, or $69.2 per hour.

Senior / Principal Machine Learning Scientist, Scientific Reasoning Models, AI for Drug Discovery

New York, NY • On-site

Genentech, Inc.
Scientific Research and Development Services • 10K+ employees
Learn more about Genentech, Inc.external

Full-time

Re-posted yesterday

Genentech rating

8.8

Company rating: 8.8 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

Job description

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning (ML) techniques. We are seeking a Senior or Principal Machine Learning Scientist to join the Foundation Models team within Prescient Design (gRED). In this role, you will drive the development of our internal reasoning Large Language Models (LLMs) and enable it to succeed at drug discovery tasks, including biomolecular design. You will work at the intersection of engineering and research, designing and scaling large machine learning systems.
In this role, you will:
  • Technical Leadership & Strategy: Lead the design and evolution of scientific reasoning systems, setting technical direction for model architectures, training strategies, and evaluation methodologies.
  • Model Capability & Improvement: Define and execute approaches to systematically improve model performance on scientific tasks, including long-horizon reasoning and complex decision-making.
  • Domain Translation: Translate biological and chemical domain knowledge into machine learning objectives, training signals, and evaluation criteria, working closely with domain experts.
  • Scalable Systems & Engineering: Architect and improve large-scale distributed machine learning systems, ensuring robustness, efficiency, and reproducibility across training and evaluation workflows.
  • Research-to-Production Impact: Partner with researchers and cross-functional teams to move models from research prototypes to production-ready systems that support active discovery programs.

As a Senior ML Scientist:
  • You are the primary driver of technical implementation for scientific reasoning, translating high-level research goals into robust training code.
  • You own the end-to-end integrity of large-scale training runs, from data orchestration to the development of rigorous reasoning benchmarks.
  • You act as a technical mentor to junior staff and interns, fostering a culture of engineering excellence and rapid experimentation.

As a Principal ML Scientist:
  • You help define the long-term technical roadmap for scientific reasoning models, identifying new opportunities and setting priorities across initiatives.
  • You architect new initiatives that integrate diverse data modalities, guiding the technical direction of cross-functional projects across gRED.
  • You serve as a key technical authority for leadership, influencing how Genentech leverages generative AI to solve high-stakes problems in the therapeutic pipeline.

Who you are
  • PhD in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
  • Experience:
    • For Senior (SE6): 0 - 2+ years of industry or post-doc experience with a focus on deep learning.
    • For Principal (SE7): 5+ years of industry or post-PhD experience with a demonstrated track record of technical leadership and project ownership.
  • LLM Expertise: Extensive experience developing and training large-scale machine learning models, including approaches to improve domain understanding, reasoning capabilities, and model alignment.
  • Publication Record: A strong history of research excellence at top-tier venues (e.g., NeurIPS, ICLR, ICML).
  • Engineering: Strong software engineering skills and experience designing and operating large-scale or high-performance machine learning systems.

Preferred
  • Experience with molecular modalities (e.g., protein sequences, chemical graphs, and structured molecular data) is highly valued but not required.
  • A public portfolio of research or significant contributions to open-source ML libraries.
  • A passion for applying frontier AI to drug discovery.

Relocation benefits are NOT available for this job posting
The expected salary range for this position, based on the primary location of San Francisco, is $167,400 - 310,800 of hiring range for the Senior Scientist, and $194,000 - 360,400 for the Principal Scientist. For the primary of location of New York City, $160,100 - 297,300 for the Senior Scientist, and $185,600 - 344,600 for the Principal Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
#ComputationCoE
#tech4lifeComputationalScience
#tech4lifeAI
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

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About Genentech

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A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.

Industry

Scientific research and development services

Company size

10,000+ Employees

Headquarters location

South San Francisco, CA, US

Year founded

1976

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