Senior Machine Learning (ML) Engineer (AI Insurtech)

EvolutionIQ; New York (NY); On-site; USD 190,000 - 225,000; Full time

Benefits offered by this job

Annual bonus

Company equity (RSUs)

Medical, dental, vision

401k matching

Parental leave

Job summary

EvolutionIQ is seeking a Senior Machine Learning Engineer in New York to build production ML models and translate client problems into robust data solutions. You’ll explore data deeply, design scalable features, and contribute to end-to-end model development with NLP and time-series capabilities.

You will collaborate across teams, deploy models, and advance ML strategies in a fast-growing environment. A competitive package includes a base salary, bonus, and RSUs.

Qualifications

• 2+ years of experience as a Machine Learning Engineer or Data Scientist in scalable production environments.
• Strong experience with Python data stack (Pandas, Jupyter) and ML frameworks (sklearn, Keras, PyTorch).
• Excellent written and verbal communication across technical and non-technical audiences.
• Team player who is solutions-oriented.
• Experience leveraging Claude Code and related tools is a strong plus.

Responsibilities

• Build ML models for production use.
• Perform in-depth exploratory data analysis to scope ML opportunities and lay groundwork for model design and evaluation.
• Suggest and implement new features to improve model performance and business logic.
• Write and review production-quality PRs daily.
• Translate client business problems into ML problems.
• Build scalable ML models for claim time series forecasting and NLP text understanding.
• Grow in data and ML space solving large-scale structured and unstructured datasets.

Skills

Python

Pandas

Jupyter

scikit-learn

Keras / PyTorch

Data analysis

Model deployment

Team collaboration

Tools

Dagster

BigQuery

Vertex AI

GCP

Terraform

Spark

Kubernetes

Job description

About Us:

EvolutionIQ’s mission is to deliver state of the art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient, so that more people impacted by injury or illness can continue their lives with dignity and stability. We are currently experiencing massive growth and to accomplish our goals, we are hiring world‑class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row and Built In’s Best Places to work in 2025 and 2026!

About You

A Senior Machine Learning Engineer who thrives on first principles problems that no one has ever worked on before. You love innovation and making an immediate impact, and are constantly driving toward launch and delivery thanks to your high degree of ownership and control. You love working on new and challenging problems, not incremental or marginal improvements, and you're supercharged by having interesting, unsolved problems continually present themselves.

In This Role, You Will

• Build ML models for production use
• Perform in-depth exploratory data analysis to scope ML opportunities, identify potential issues in the data, and lay the groundwork for model design, training & evaluation strategies
• Suggest and implement new features to improve model performance and business logic
• Write and review production-quality PRs daily
• Translate client business problems into ML problems
• Build scalable machine learning models for claim time series forecasting and NLP text understanding
• Continue to grow and learn in the data & ML space with a focus on business problems that require making sense of large-scale structured and unstructured datasets

Requirements

• 2+ years of experience as a Machine Learning Engineer or Data Scientist, preferably in highly scalable production environments.
• You have deep exposure to data science & ML tech stacks (sklearn, Keras / PyTorch, tuning frameworks), data analysis & modeling, feel at home in Python/Pandas/Jupyter, and strive for scalable technical concepts and solutions.
• You have excellent written and verbal communication skills and can effectively correspond between technical and non-technical audiences.
• You’re a team player who is solutions-oriented.
• Experience leveraging Claude Code and related tools is a strong plus

Even Better If You Have The Following

• Knowledge of Dagster, BigQuery, Vertex AI, GCP, Terraform, Spark, Kubernetes
• Owned and deployed, and maintained model-serving pipelines in production
• Expert skills at writing clean, efficient, and easy-to-understand code with unit tests and functional design patterns
• Experience with advanced statistical modeling, especially probabilistic programming
• Ambitious, collaborative, and empathetic values
• A work style that is open to giving and receiving critical feedback and collaborating effectively across teams

Work-life, Culture & Perks

• Compensation: The base salary range is $190-225K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package.
• Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits.
• Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work.
• Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend.
• Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement.
• Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer.

EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.