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Machine Learning Engineer Biotech Jobs in Fort Mill, SC

The Hartford

Senior AI Machine Learning Engineer

Charlotte, NC · On-site

$119K - $157K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Euclid Innovations

ML Engineer

Charlotte, NC · On-site

Euclid Innovations is seeking a skilled and experienced Machine Learning Engineer to design and implement solutions for extracting, processing, and storing information from large-scale document ...

Varsity Tutors

Machine Learning Tutor

Matthews, NC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Charlotte, NC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$68 - $73/hr

Senior AI Platform Engineer (Contract) We are not accepting C2C or 1099 arrangements. Location ... Design, develop, and deploy scalable AI, Machine Learning, Generative AI, and Predictive AI ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Fort Mill, SC

Machine Learning Engineer Biotech information

See Fort Mill, SC salary details

$27.7K

$113.2K

$170K

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

As of Sep 14, 2026, the average yearly pay for machine learning engineer biotech in Fort Mill, SC is $113,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,200.00 and $136,200.00 per year, depending on experience, location, and employer.

What does a machine learning engineer do in biotech?

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?

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 popular job titles related to Machine Learning Engineer Biotech jobs in Fort Mill, SC?

For Machine Learning Engineer Biotech jobs in Fort Mill, SC, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Biotech jobs in Fort Mill, SC look for?

The top searched job categories for Machine Learning Engineer Biotech jobs in Fort Mill, SC are:

What cities near Fort Mill, SC are hiring for Machine Learning Engineer Biotech jobs?

Cities near Fort Mill, SC with the most Machine Learning Engineer Biotech job openings:

Machine Learning Engineer Biotech jobs near you

Machine Learning/AI Engineering Manager

Charlotte, NC • On-site

Vangard, Inc.
Convention and Trade Show Organizers • 11 - 50 employees
Learn more about Vangard, Inc.external

Full-time

Posted 10 days ago

Job description

We are seeking a Machine Learning Engineering Manager to lead a high-performing team of Machine Learning Engineers responsible for building, operating, and evolving Vanguard's production AI, ML, and Generative AI solutions.

This leader will oversee engineering for a portfolio of traditional machine learning and GenAI capabilities that power investor personalization, financial planning, and advice experiences across Personal Wealth Technology. You will partner closely with Data Scientists, Product Owners, Architects, and Vanguard's Investment Strategy Group (ISG) methodology teams to transform sophisticated models and research into reliable, scalable, and trusted production solutions.

This is a highly technical leadership role. The successful candidate will be expected to actively participate in solution architecture, technical design, engineering strategy, model operations, production support, and Agile delivery while developing the next generation of AI engineering talent.

Responsibilities

  • Lead a team of Machine Learning Engineers delivering scalable, secure, reliable, and extensible AI solutions
  • Develop, maintain, support, and evolve a portfolio of production machine learning and generative AI models
  • Partner with Investment Strategy Group methodology teams to operationalize financial advice, portfolio construction, and personalization models
  • Ensure production readiness through monitoring, alerting, validation, testing, observability, and incident management practices
  • Drive engineering excellence, DevOps, MLOps, LLMOps, and FinOps disciplines
  • Shape AI and ML roadmaps alongside Data Scientists, Product Owners, and stakeholders
  • Provide technical direction and architectural guidance for complex AI and ML initiatives
  • Build trusted relationships across technology and business teams to influence strategy and delivery outcomes
  • Establish standards and best practices that enable safe, trustworthy, explainable, and scalable AI solutions
  • Drive adoption of GenAI and agentic solutions within the engineering organization to improve efficiency, automation, and delivery quality
  • Hire, coach, mentor, and develop future technical leaders

What You'll Own

  • Delivery, operation, and continuous improvement of Vanguard's production AI, ML, and GenAI platforms and solutions
  • Engineering ownership along with ISG Methodology for the Vanguard Financial Advice Model (VFAM) and Risk-Based Research Engine (RBRE)
  • Model health monitoring, observability, availability, and operational excellence across all production models
  • Reliability and support processes ensuring production AI systems remain resilient, trusted, and available
  • Technical leadership for Machine Learning Engineering, MLOps, LLMOps, DevOps, and FinOps practices
  • Team leadership, coaching, and development for a high-performing Machine Learning Engineering organization
  • Stakeholder relationships across Technology, Methodology, Product, and Analytics teams

Qualifications

  • Minimum of eight years data analytics, programming, database administration, or data management experience.
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

Preferred Qualifications

  • Proven experience leading Machine Learning, AI Engineering, or Software Engineering teams
  • Strong technical depth in production AI/ML systems and cloud-native engineering
  • Experience establishing operational excellence for production AI platforms
  • Demonstrated success partnering with product, analytics, and business stakeholders
  • Passion for developing engineering talent and building high-performing teams
  • Ability to balance strategic leadership with hands-on technical engagement
  • Interest in advancing modern engineering practices, including MLOps, LLMOps, FinOps, and agentic AI

Why This Role

  • Directly influence how Vanguard delivers personalized financial advice at scale
  • Lead engineering for some of Vanguard's most strategic AI and machine learning capabilities
  • Work at the intersection of financial methodology, applied AI, and large-scale engineering
  • Shape the future of GenAI, agentic systems, and AI engineering practices within Personal Wealth Technology
  • Develop a talented team while driving meaningful outcomes for millions of investors
  • Join a leadership team committed to innovation, engineering excellence, and investor-centric outcomes

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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