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Senior Machine Learning Software Engineer Jobs (NOW HIRING)

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site

$147.40K - $194.30K/yr

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine ... Collaborate closely with ML scientists and software engineers to understand current challenges and ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Strive Works

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121.40K - $160K/yr

Senior Machine Learning Engineer Austin, Texas or Remote Build, Deploy, and Maintain AI for an ... You will work alongside data scientists, software engineers, and DevOps engineers to transform ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147.40K - $194.30K/yr

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine ... Collaborate closely with ML scientists and software engineers to understand current challenges and ...

Taskrabbit

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144.30K - $190.30K/yr

As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how ... Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Taskrabbit

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144.30K - $190.30K/yr

As a Senior Machine Learning Engineer, you will tackle exciting challenges that directly impact how ... Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and ...

Attentive

Senior Machine Learning Engineer

New York, NY · On-site

$244K - $320K/yr

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... machine-learning software systems * Proven experience owning ML systems long enough to see the ...

Button, Inc.

Senior Machine Learning Engineer

$153K - $198K/yr

You will work closely with product managers, data scientists, and software engineers to translate ... AS A SENIOR MACHINE LEARNING ENGINEER, YOU WILL: * Own the full ML lifecycle including feature ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... As a Senior Machine Learning Engineer in Product & Technology, you will help Paylocity build and ...

Button

Senior Machine Learning Engineer

Manhattan, NY · On-site

$153K - $198K/yr

You will work closely with product managers, data scientists, and software engineers to translate ... AS A SENIOR MACHINE LEARNING ENGINEER, YOU WILL: Own the full ML lifecycle including feature ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... As a Senior Machine Learning Engineer in Product & Technology, you will help Paylocity build and ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110.90K - $152.40K/yr

This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices. The Senior ML Engineer will ...

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Senior Machine Learning Software Engineer information

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$75.5K

$143.3K

$192K

How much do senior machine learning software engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for senior machine learning software engineer in the United States is $143,292.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,500.00 and $161,500.00 per year, depending on experience, location, and employer.

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

A Senior Machine Learning Software Engineer requires deep expertise in machine learning algorithms, statistical analysis, and strong programming skills in languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, as well as experience with cloud platforms and version control systems, is standard. Exceptional problem-solving, leadership, and communication skills help drive project success and mentor junior engineers. These competencies are crucial for designing scalable ML solutions, ensuring code quality, and effectively collaborating within cross-functional teams.

What are some common challenges Senior Machine Learning Software Engineers face when deploying models to production?

Senior Machine Learning Software Engineers often encounter challenges such as ensuring model scalability, maintaining performance under real-world data conditions, and integrating models seamlessly with existing systems. Handling data drift and monitoring model predictions for accuracy over time are also critical responsibilities. Collaboration with data engineers, DevOps, and product teams is essential to address these challenges and ensure robust, reliable deployments.

What is a Senior Machine Learning Software Engineer?

A Senior Machine Learning Software Engineer is an experienced professional who designs, develops, and deploys machine learning models and systems to solve complex problems. They work closely with data scientists, engineers, and other stakeholders to build scalable and efficient solutions that leverage large data sets and advanced algorithms. Their responsibilities often include architecting ML pipelines, optimizing model performance, and mentoring junior team members. Typically, they have a strong background in computer science, programming, and applied mathematics, along with several years of hands-on experience in machine learning and software engineering.

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

AspectSenior Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, integrates algorithms into products, collaborates with engineering teamsAnalyzes data, builds statistical models, visualizes insights, collaborates with business teams
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, healthcare

While both roles involve working with data and algorithms, Senior Machine Learning Software Engineers focus on developing and deploying scalable ML models within software systems, whereas Data Scientists primarily analyze data to generate insights and inform business decisions.

More about Senior Machine Learning Software Engineer jobs
What cities are hiring for Senior Machine Learning Software Engineer jobs? Cities with the most Senior Machine Learning Software Engineer job openings:
What are the most commonly searched types of Machine Learning Software Engineer jobs? The most popular types of Machine Learning Software Engineer jobs are:
What states have the most Senior Machine Learning Software Engineer jobs? States with the most job openings for Senior Machine Learning Software Engineer jobs include:
What job categories do people searching Senior Machine Learning Software Engineer jobs look for? The top searched job categories for Senior Machine Learning Software Engineer jobs are:
Senior Machine Learning Software Engineer jobs near you
Infographic showing various Senior Machine Learning Software Engineer job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 95% Full Time, 3% Part Time, and 1% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $143,292 per year, or $68.9 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Freenome

Brisbane, CA • On-site

$147.40K - $194.30K/yr

Full-time

Posted 12 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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