Job summary
Job post source
This job is directly from EvolutionIQ
Job overview
The Staff Machine Learning Engineer at EvolutionIQ leads the development and deployment of scalable ML models to solve complex insurance-related problems, driving innovation and business impact.
Responsibilities and impact
The role involves exploratory data analysis, feature engineering, collaborating with product and engineering teams, mentoring junior engineers, building production ML models, and translating business problems into ML solutions.
Compensation and benefits
The compensation range is $225K-$250K with flexibility, including equity, full medical, dental, vision, disability insurance, 401k matching, paid parental leave, flexible PTO, hybrid work options, catered lunches, and professional development funds.
Experience and skills
Candidates need 5+ years in ML engineering with production experience, strong skills in Python, ML frameworks, leadership experience managing teams, and ability to translate research into production code; knowledge of GCP, Kubernetes, and advanced modeling is a plus.
Career development
The company offers $1,000/year for professional development and internal upskilling opportunities to support growth.
Work environment and culture
EvolutionIQ values diversity, inclusion, collaboration, and work-life balance with a pet-friendly office, flexible schedules, and a supportive environment.
Company information
EvolutionIQ focuses on improving outcomes for injured workers through AI-driven insurance solutions and has been recognized as a top workplace for three consecutive years.
Team overview
The candidate will join a collaborative team working on high-impact ML projects with opportunities to mentor and lead junior engineers.
Job location and travel
The position offers a hybrid work environment with a pet-friendly office and catered events.
Unique job features
This role involves working on cutting-edge ML problems in insurance, including time series forecasting, NLP, and generative AI, with a strong emphasis on innovation and production readiness.
Company overview
EvolutionIQ is a technology company specializing in artificial intelligence and machine learning solutions for the insurance industry. They develop advanced AI-driven platforms that help insurers automate claims processing, detect fraud, and improve overall operational efficiency. Founded in 2019, EvolutionIQ has quickly gained recognition for its innovative approach, securing partnerships with major insurance firms and attracting significant venture capital investment. The company's mission is to revolutionize the insurance sector by leveraging cutting-edge technology to enhance decision-making and customer experiences.
How to land this job
Position your resume to highlight your leadership in ML engineering, especially your experience leading teams and deploying scalable production models, which aligns with EvolutionIQ's need for a seasoned expert who can drive impact from idea to production.
Emphasize your proficiency with Python, data science and AI tech stacks like sklearn, PyTorch, and generative AI frameworks, as well as your ability to translate complex business problems into ML solutions, reflecting the core responsibilities of the role.
Apply through multiple platforms including EvolutionIQ’s corporate careers page and LinkedIn to maximize your application visibility and increase your chances of being noticed by recruiters.
Connect with current ML engineers and product stakeholders at EvolutionIQ on LinkedIn; use ice breakers such as commenting on recent AI projects they’ve shared or asking about their approach to integrating generative AI into insurance solutions to open dialogue.
Optimize your resume for ATS by incorporating keywords from the job description such as 'scalable production environments,' 'model-serving pipelines,' 'LLM/gen AI frameworks,' and 'technical leadership' to ensure it passes initial automated screenings.
Utilize Jennie Johnson’s Power Apply feature to automate tailored resume submissions, identify multiple application channels, and find relevant LinkedIn contacts for networking, allowing you to focus your energy on preparing for interviews and refining your skills.
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