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Associate Applied AI Engineer

Hologic
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We are hiring an Associate Applied AI Engineer to help us find and deliver practical AI solutions across the company. This is an early-career, hands-on role where you will learn the full life of a project alongside experienced engineers: understanding a business problem, deciding whether and how AI can help, building the solution, getting it into production and making sure people actually use it. Everything we build is designed to help our employees and business teams work better, so that we can ultimately deliver the best healthcare solutions to our patients and customers.

You will split your time between business-facing work and hands-on building, with teams that support our most critical Hologic business strategies. Some weeks that means joining discovery sessions and mapping how a process works today. Other weeks it means writing code or configuring a platform. We care more about solving the problem well than about which tool you used to solve it.

We do not expect you to know everything on day one. We do expect curiosity, a habit of asking good questions and a drive to learn quickly. You will start with well-scoped pieces of real projects and take on more ownership as your skills and confidence grow.

What You Will Do

Member of High Performing Team

  • Work alongside business and technical teams to find opportunities where AI can genuinely help (and where it can’t). Absolute intellectual and technical honesty is needed.
  • Take part in discovery sessions: ask questions, take clear notes and help map how the work gets done today.
  • Help define what success looks like for each project, including the measures we will use to show it worked.
  • Turn discovery notes into clear problem statements and options that the team can review and act on.

Design and build

  • Build features, prototypes and components for AI solutions such as copilots, agents, retrieval-augmented generation (RAG) applications and workflow automations, on the platforms we use today, including Azure OpenAI, Claude and Microsoft Copilot.
  • Write code in Python, JavaScript/TypeScript or C#, and learn when configuration on platforms like Power Automate or Logic Apps is the better fit.
  • Practice solid engineering habits from the start: version control, testing, CI/CD and evaluation of AI output quality, with guidance and code reviews from senior engineers.
  • Help integrate solutions with our enterprise systems, data and APIs, with security considered from the start.
  • Help move projects from prototyping (Minimal Viable Projects, or MVPs) through deployment, adoption, support and iterative improvement, building toward owning the outcome, not just the code.

Make it enterprise-ready

  • Learn how we get solutions ready for production by working with our security, architecture, governance and compliance teams.
  • Learn to weigh trade-offs like cost, performance, reliability and maintainability, and practice explaining them in plain business terms.
  • Help set up monitoring and feedback loops, and track whether solutions are being used and delivering value.
  • Support adoption of what the team builds through demos, training materials and feedback sessions.

Learn and share

  • Explain what you built, and what AI can and cannot do, clearly to technical and non-technical audiences.
  • Document your designs and decisions so others can support and build on your work.
  • Take part in code and design reviews, giving and receiving feedback openly.
  • Bring new ideas, tools and techniques from the AI community back to the team.

How You Will Grow

  • Work side by side with senior engineers on live projects, with regular code and design reviews.
  • Get hands-on experience with enterprise AI platforms, including our Azure environment, from your first weeks.
  • Build business skills such as running discovery, defining success measures and presenting to stakeholders.
  • Take on larger and more independent pieces of work as you grow, with a clear path toward owning solutions end to end.

What We Are Looking For

  • Bachelor’s or Master’s degree in computer science, software engineering, data science, computer engineering or a related technical field (completed by your start date), or equivalent practical experience.
  • Up to two years of professional experience. Internships, co-ops, research roles, capstone, hackathon and personal projects all count.
  • Solid programming fundamentals in Python, plus familiarity with JavaScript/TypeScript, C# or a similar language, and a willingness to use low-code platforms when they are the better fit.
  • Working knowledge of core AI concepts, including large language models (LLMs), embeddings, RAG, agents, prompt engineering and evaluation, plus hands-on experience building with LLMs through coursework, projects or internships.
  • Curiosity about the frontier model landscape, including Claude, OpenAI and Gemini models and the leading open-source models, and an interest in what each is good at.
  • Familiarity with software engineering basics: Git, testing, APIs and working with data (for example, SQL).
  • Exposure to a major cloud platform through coursework, projects or internships, with Azure strongly preferred. We run many of our AI solutions on our own Azure infrastructure, so you will be working in it from day one, and we will help you ramp up.
  • At least one project you have taken from idea to a working demo or deployed tool and can walk us through. A link to your GitHub or portfolio is welcome.
  • Clear communication with both technical and business audiences, and the confidence to ask questions when something is unclear.
  • A strong desire to learn, take feedback and grow, with evidence that you pick up new tools quickly.
  • Ability to thrive in a fast-paced, dynamic environment where teamwork, collaboration, communication and respect are paramount.

Nice To Have:

  • Internship or co-op experience in software, data, ML or AI engineering.
  • A project you have shipped that real people use, even a small one.
  • Exposure to orchestration frameworks such as LangGraph or Semantic Kernel, or to Model Context Protocol (MCP).
  • Experience with Power Platform or similar low-code workflow automation tools.
  • Familiarity with containers (for example, Docker), CI/CD pipelines or cloud deployment.
  • A Microsoft Azure certification, such as an Azure fundamentals or Azure AI certification.
  • Coursework, projects or interest in applying AI or analytics in Quality (quality systems, complaint handling, CAPA, audits) or Commercial (sales, marketing, pricing, customer analytics) settings.
  • Exposure to business analysis, consulting or product management through coursework, internships, case competitions or student organizations.
  • Interest in applying AI responsibly in an FDA-regulated environment.

The annualized base salary range for this role is $75,900 to $118,800 and is bonus eligible. Final compensation packages will ultimately depend on factors including relevant experience, skillset, knowledge, geography, education, business needs, and market demand.

Why Hologic?

We are committed to making Hologic the company where top talent comes to grow. For you to succeed, we want to enable you with the tools and knowledge required and so we provide comprehensive training when you join as well as continued development and training throughout your career.

If you have the right skills and experience, apply today!

Agency and Third Party Recruiter Notice:

Agencies that submit a resume to Hologic must have a current executed Hologic Agency Agreement executed by a member of the Human Resource Department. In addition, Agencies may only submit candidates to positions for which they have been invited to do so by a Hologic Recruiter. All resumes must be sent to the Hologic Recruiter under these terms or they will not be considered.

Hologic, Inc. is proud to be an Equal Opportunity Employer inclusive of disability and veterans.