ML Engineer

About us Itero Group is a Women-Owned Small Business focused on simplifying complex transformations. We empower clients in the private and government sectors to become more optimized, digitally enabled, and data-driven organizations through our comprehensive business consulting and innovative delivery solutions.

Our dedicated team members are experienced thought leaders, tenacious workers, and creative thinkers. We hire people who are passionate about being catalysts for change— in our company, for our clients, throughout our careers—and we empower people to express their ideas, create better practices, innovate better products, and become better professionals. We have been named a Great Place to Work for six years, and offer a competitive salary and benefits package.

As a Machine Learning Engineer, you will be the architect of our technical evolution. We have a proven product and strong models, but we are ready to mature our technology to support increasing demand and remain agile to combat evolving scam tactics. You will have the autonomy to design, build, and own the end‑to‑end machine learning infrastructure that ensures our systems are robust, scalable, and secure.

• Pipeline Architecture & Automation: Lead the migration of our modeling workflows from notebooks and scripts to fully automated, production‑grade ML pipelines. Define how we train, version, and deploy models at scale.
• Privacy Engineering: Collaborate with Data Engineers to design and enhance our privacy‑preserving data pipelines. Ensure that PII is detected and anonymized effectively before it reaches our training environments or is retained.
• Infrastructure as Code: Champion the use of AWS CDK (or Terraform) to define our ML infrastructure, ensuring our training and inference environments are reproducible and resilient.
• Model Expansion: Collaborate with the CDO to expand our technical capabilities, including building the foundation for multi‑lingual fraud detection and hybrid rule‑based/ML systems.
• Operational Excellence: Implement best practices for MLOps, including automated rollback strategies, drift detection, and continuous performance monitoring.

• 3‑5 Years of
  
  Experience:
  
  Proven background in Machine Learning Engineering (or Data Science with a heavy software engineering focus).
• Sage Maker Native: Deep expertise within the AWS ML ecosystem, specifically in migrating workflows from Sage Maker Studio Notebooks to automated Pipelines.
• Strong Python Engineering: Write clean, modular, and tested code. Comfortable refactoring research code into production‑grade software.
• MLOps Fundamentals: Experience implementing CI/CD for machine learning, including automated rollback strategies and model drift detection.
• Infrastructure as Code: Hands‑on experience defining infrastructure using AWS CDK or Terraform.

• NLP & PII
  
  Experience:
  
  Familiarity with Named Entity Recognition (NER) for PII redaction and working with modern text classification architectures (BERT, RoBERTa).
• Multi‑Lingual NLP: Experience training, fine‑tuning, or deploying models for non‑English languages.

• Bachelor’s or advanced degree in Computer Engineering, Computer Science, Electrical Engineering, or a closely related technical field.

If you are looking for a role where you will lead with integrity, create and innovate, inspire excellence, be a respected member of the team, drive results, and have fun, we look forward to connecting with you!

• Health & Wellness: Medical (BC‑BS), dental, and vision plans to suit your needs.
• Paid Time Off: Generous PTO, paid holidays, and increasing PTO based on years of service.
• Retirement Savings: 401(k) plan with company match and auto‑enrollment.
• Company‑Paid Coverage: Short‑term and long‑term disability, life insurance, and AD&D insurance.
• Additional Options: Voluntary benefits including pet insurance and student loan assistance up to $1,000 annually.
• Perks: FSAs, HSAs, wellness programs, and more to enhance your work‑life balance.

Itero Group is an equal opportunity employer and does not discriminate against any employee or applicant because of race, age, sex, color, physical or mental disability, religion, sexual orientation, marital status, national origin, veteran status or political affiliation.