Machine Learning (ML) Engineer

About Us: EvolutionIQ’s mission is to improve the lives of injured and disabled workers and enable them to return to the workforce, saving billions of dollars in avoidable costs and lost productivity to the US and global economies and make insurance more affordable for everyone. 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!

About You: A ML 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:

• You are an ML Engineer / Data Scientist with 2 years of experience, 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’re a team player who is solutions-oriented.
• You have crisp written and verbal communication skills and can effectively correspond between technical and non-technical audiences.

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 compensation range for this role is 160-180K depending on experience, as well as meaningful equity plan.
• Well-Being: Full medical, dental, vision, short- & long-term disability, 401k matching. 100% of the employee contribution up to 3% and 50% of the next 2%.
• Home & Family: Flexible PTO, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers), sick days, paid time off. For new parents returning to work we offer a flexible schedule. We also offer sleep training to help you and your family navigate life schedules with a newborn.
• Office Life: Ability to work hybrid. Catered lunches, happy hours, and pet-friendly office space, and home office stipend. 
• Growth & Training: $1,000/year for each employee for professional development, as well as upskilling opportunities internally
• Sponsorship: We are open to sponsoring candidates currently in the US who need to transfer their active H1-B visa.

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