Machine Learning Engineer

We are constantly looking to add to our core talent. If you are seeking a career that is challenging and rewarding, a work environment that is diverse and dynamic, look no further — Haemonetics is your employer of choice.

Job Details

Key Responsibilities:

• Applied Machine Learning: Implement practical ML solutions. This involves training "classic" models (regression, classification) or integrating off-the-shelf models and APIs, rather than researching deep learning architectures from scratch.

• Data Discovery & Preparation: Analyze mixed datasets (structured SQL data, logs, and unstructured inputs) to determine if they are viable for automation or prediction. You will be the first to "view" this data with an ML lens.

• Integration & Prototyping: Build Python-based services (e.g., wrapping models in APIs) and collaborate with the core Software Team to integrate these predictions into our .NET enterprise applications.

• Technical Validation: Review and validate technical deliverables from external AI consultants to ensure they are sound, maintainable, and properly documented.

• Regulated Engineering: Ensure all ML code and data handling processes comply with strict regulatory standards (e.g., rigorous version control, data privacy/HIPAA, and documentation).

Required Knowledge, Skills, & Capabilities:

• Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.

• Experience: Minimum of 3-4 years of professional software development experience, with demonstrable experience in Data Science or Machine Learning projects.

• The "Python Stack": proficiency with Python and standard libraries (Pandas, NumPy, Scikit-learn) is required.

• Versatility: You are comfortable wearing multiple hats. You might be cleaning data on Monday, tweaking a regression model on Tuesday, and writing a Python API wrapper on Wednesday.

• Independence: Ability to work as the sole ML practitioner within a Scrum team of C# developers. You can research problems and unblock yourself without a senior Data Scientist sitting next to you.

• General Software Skills: Familiarity with version control (Git), APIs (REST), and basic software design principles.

Desired Assets (Nice to have):

• Experience working in a regulated industry (Medical Device, Pharma, Finance, etc.) or knowledge of standards like IEC 62304, ISO 13485, or HIPAA.

• Familiarity with C# / .NET (you don’t need to be an expert, but you need to be able to read the code and work with the team that writes it).

• Exposure to cloud environments (AWS preferred) for deploying simple services.

General Skills:

• Pragmatic: You prefer a simple solution that works over a complex one that is theoretically perfect.

• Curious: You are excited to dig into complex medical data to find patterns.

• Communicator: You can explain data concepts to stakeholders who do not have a math background.

EEO Policy Statement

Pay Transparency:

The base pay actually offered to the successful candidate will take into account, without limitation, the candidate’s location, education, job-knowledge, skills, and experience in prior relevant roles. Incentives may also be provided as part of Haemonetics’ employee compensation. For sales roles, employees will be eligible for sales incentive (i.e., commission) under the applicable plan terms. For non-sales roles, employees will be eligible for a discretionary annual bonus, the target amount of which varies based on the applicable role, to be governed by the applicable plan terms. Employees may also be eligible to participate in the Company’s long-term incentive plan, with eligibility and target amount dependent on the role.

In addition to compensation, the Co