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Machine Learning Engineer Biotech Jobs in Chicago, IL

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off-sites * Equipment and learning budget to help you do your best work and keep up with ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and offsites * Equipment and learning budget to help you do your best work and keep up with the ...

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : • PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

Showing results 41-60

Machine Learning Engineer Biotech information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

How much do machine learning engineer biotech jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning engineer biotech in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 per year, depending on experience, location, and employer.

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?

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech 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 Chicago, IL? The most popular types of Machine Learning Engineer Biotech jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Machine Learning Engineer Biotech jobs? Cities near Chicago, IL with the most Machine Learning Engineer Biotech job openings:
Infographic showing various Machine Learning Engineer Biotech job openings in Chicago, IL as of July 2026, with employment types broken down into 92% Full Time, 1% Part Time, 1% Temporary, and 6% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $132,651 per year, or $63.8 per hour.
Manager Machine Learning Engineering

Manager Machine Learning Engineering

Paylocity

Schaumburg, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 23 days ago


Paylocity rating

7.7

Company rating: 7.7 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

152nd of 454 rated business services


Job description

Description:

Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.


While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.


We give our employees what they need to succeed, including great benefits and perks! We offer medical, dental, vision, life,

disability, and a 401(k) match, as well as perks that support you, your family, and your finances. And if it’s career development you desire, we provide that, too! At Paylocity, people matter most and have always been at the heart of our business.


Help Paylocity enhance communication and enable employees to connect, collaborate, and create from anywhere with a position in Product & Technology!


Want to develop the strategies and principles needed to deliver compelling software? Join our team and help us enhance our all-in-one software platform, elevate our one-of-a-kind technology, and improve the employee experience?


Take your career to the next level at one of G2's Top 100 Software Companies. Explore our Product & Technology positions to see where you fit!


This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements


Manager Machine Learning Engineering


Position Overview

Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users.


Our team is:

  • Building infrastructure that can power ML and AI features for millions of users
  • Building and deploying platform-wide recommendations to help companies follow HR best practices and allow employees to get the most out of our platform (Paylocity AI page)
  • Baking AI Ethics into all our processes as a first-class citizen (Blog Post)
  • Working in a collaborative fully remote environment with a desire to share ideas and continuously improve
  • Invested in staying current in machine learning engineering by applying the newest tools, technologies, and practices
  • Excited to work on cutting-edge technology!

Primary Responsibilities

The Manager, Machine Learning Engineering (MLE) has a critical role in our Product and Technology organization. This role requires strong technical expertise as well as strong people and project management experience. This leader will be responsible for helping shape the direction of AI/ML initiatives and driving delivery of business outcomes, while actively investing in the growth and development of team members through coaching, mentorship, and career planning. This position requires commitment to exceptional results, a strong desire for continuous improvement, and the ability to build a collaborative high performing culture within and across teams.

A MLE Manager will be expected to:

  • Independently lead Machine Learning Engineering teams in the development and enhancement of our machine learning infrastructure and solutions that impact millions of employees every day.
  • Build and evolve AI platforms that scale across products, domains, and teams at Paylocity.
  • Own and drive end-to-end ML tooling and automation, from infrastructure and data pipelines to model deployment, monitoring, and optimization.
  • Collaborate with data science and engineering teams to drive adoption of best practices in MLE while contributing to the development of formal training programs and materials for MLE tool adoption.
  • Influence and collaborate with other teams across Product & Technology (e.g. Data Engineering, Cloud Center of Excellence, Platform teams, Architecture Review Board, etc.) to ensure alignment and integration of ML capabilities.
  • Influence business strategy by leveraging data and metrics and presenting recommendations and insights to Dir+ leadership.
  • Mentor, coach, and develop teams, fostering technical excellence, professional growth, and leadership capabilities.
  • Oversee and manage multiple projects simultaneously, ensuring alignment with company objectives, resource optimization, and timely delivery.
  • Establish best practices for scalable and reproducible machine learning development, deployment, and governance.
  • Continuously assess team outcomes, processes, and quality to drive improvements.
  • Stay at the forefront of AI and ML advancements, ensuring the team continuously evolves by incorporating the latest technologies, methodologies, and best practices.

Education and Experience

  • Bachelor’s degree in a quantitative field is required
  • 5+ years of hands-on AI/ML success at software companies
  • 2+ years of experience managing and leading data teams, with demonstrated success in coaching, mentoring, and developing talent
  • Experience in writing production grade machine learning infrastructure and/or models in Python
  • Hands-on experience with cloud infrastructure on AWS (Glue, EMR, Lambda, etc.) and infrastructure-as-code tooling
  • Familiar with cloud-based source code management, continuous integration, continuous delivery, and other software development best practices (GitHub Actions, TeamCity, Octopus, Jenkins, etc.)
  • Demonstrated ability to lead high-performing teams, inspire others, and drive business results
  • Skilled at translating business problems into data/ML problems and communicating the results to non-technical audiences
  • Self-motivated, adaptable, and highly detail oriented
  • Must have a strong sense of curiosity and a willingness to learn
  • Exceptional verbal and written communication skills

Preferred Skills:

  • Advanced degree (Master's or PhD) preferred in machine learning engineering, computer science, engineering, data science, statistics, mathematics, or another quantitative field.
  • Professional or academic experience in HR, social science or psychology
  • Be invested in staying current in AI/ML by applying new technologies and practices

Physical requirements

  • Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
  • Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.


Paylocity is an equal-opportunity employer.

Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.


We embrace and encourage our employees’ differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.


We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact accessibility@paylocity.com. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.


The base pay range for this position is $173,000 - $321,200 /yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. This position is eligible for an annual bonus and restricted stock unit grant based on individual performance in addition to a full range of benefits outlined here. This information is provided per the relevant state and local pay transparency laws for the location in which this position will be performed. Base pay information is based on market location. Applicants should apply via www.paylocity.com/careers.

#LI-Tech #LI-Remote

Requirements:



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