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: As an ambitious AI / ML Engineer, you will play a key role in advancing our industry-leading medical synthesis product. You take strong ownership of your work and have a proven track record of leading projects end-to-end, from ideation and requirements gathering through architecture, implementation, deployment, and iteration. You are comfortable operating with a high degree of autonomy, making thoughtful architectural and technical decisions, and helping guide the direction of AI/ML solutions across the product. Thriving in a fast-paced startup environment, you stay current with the latest AI and machine learning research. You’re passionate about applying hybrid approaches that combine large language models (LLMs), statistical machine learning techniques, and retrieval-augmented generation (RAG) with embeddings-based models to deliver better, more reliable outcomes for our users.
In this Role You Will:
- Lead AI/ML projects end-to-end, taking ownership from initial ideation and requirements gathering through architecture, development, deployment, and ongoing optimization
- Make high-level architectural and technical decisions for AI/ML systems, balancing scalability, performance, reliability, maintainability, and business impact
- Design, build, and deploy AI-powered and LLM-driven features for our claim synthesis product, including robust extraction of key information from complex medical documents and human-in-the-loop summarization workflows
- Develop and implement hybrid machine learning solutions that leverage statistical models, LLMs, and embeddings-based retrieval techniques such as RAG to improve system accuracy, scalability, and robustness
- Write clean, scalable, and efficient code while optimizing the performance of existing AI/ML systems in production
- Collaborate closely with data labelers and subject matter experts (SMEs) to rigorously evaluate AI system outputs and continuously improve model performance
- Partner closely with Product, Engineering, and other cross-functional teams to gather requirements, define technical approaches, prioritize work, and rapidly iterate on feedback
- Provide technical leadership and guidance to other engineers, helping establish best practices and driving consistency across AI/ML solutions
- Break down complex, ambiguous problems into well-defined technical solutions and drive projects forward while balancing short-term delivery with long-term architectural considerations
- Translate cutting-edge AI/ML research and novel techniques into production-grade, reliable, and maintainable solutions that operate seamlessly in live customer environments
Skills Requirements:
- 5-8+ years of experience writing performant Python code following modern best practices
- Minimum 1 year of experience building and deploying products powered by large language models (LLMs) in fast-paced, professional environments
- Proven experience leading technical projects and driving them from concept through production deployment
- Experience making architectural decisions for AI/ML systems and evaluating technical tradeoffs across scalability, reliability, performance, and maintainability
- Hands-on experience with statistical machine learning techniques as well as hybrid approaches combining LLMs, retrieval-augmented generation (RAG), and embeddings-based models, including vector search and similarity measures
- Proven ability to build and integrate API services within service-oriented or microservice architectures
- Strong skills in evaluating and interpreting LLM outputs and AI model predictions, with a focus on aligning model behavior with real-world business and user outcomes
- Expertise in prompt engineering and fine-tuning of large language models for domain-specific applications
- Strong communication and collaboration skills, with the ability to influence technical direction and work effectively with Product, Engineering, SMEs, and other stakeholders
Bonus Points:
- Experience translating state-of-the-art AI/ML research into production code
- Comfortable collaborating with data labelers and subject matter experts to improve training data and evaluation processes
- Experience building agentic or autonomous AI systems in production
- Background working with multimodal data (e.g., images, audio)
- Experience mentoring engineers or providing technical leadership across projects or teams
Work-life, Culture & Perks:
- Compensation: The base salary range is $200-235K, 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.
Skills Required
- 5-8+ years of experience writing performant Python code using modern best practices
- At least 1 year of experience building and deploying products powered by large language models in professional environments
- Experience leading technical projects from concept through production deployment
- Experience making architectural decisions for AI/ML systems and evaluating scalability, reliability, performance, and maintainability tradeoffs
- Hands-on experience with statistical machine learning, LLMs, RAG, embeddings-based models, vector search, and similarity measures
- Ability to build and integrate API services within service-oriented or microservice architectures
- Strong ability to evaluate and interpret LLM outputs and AI model predictions against business and user outcomes
- Expertise in prompt engineering and fine-tuning large language models for domain-specific applications
- Strong communication and collaboration skills with Product, Engineering, SMEs, and other stakeholders
- Experience translating state-of-the-art AI/ML research into production code
- Experience collaborating with data labelers and subject matter experts to improve training data and evaluation processes
- Experience building agentic or autonomous AI systems in production
- Experience working with multimodal data such as images or audio
- Experience mentoring engineers or providing technical leadership across projects or teams
EvolutionIQ Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EvolutionIQ and has not been reviewed or approved by EvolutionIQ.
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Fair & Transparent Compensation — Pay is considered competitive across many roles, and the company emphasizes pay transparency. Feedback suggests compensation is a strong point supporting retention and satisfaction.
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Equity Value & Accessibility — Equity is positioned as meaningful and included in offers, with stock grants on a standard 4-year vesting schedule. This structure contributes materially to total compensation for roles such as Data Scientist and Software Engineering Manager.
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Parental & Family Support — Parental leave is generous and fully paid (commonly four months for primary caregivers and three months for secondary), with flexible return-to-work support. Additional family benefits include childcare and fertility support alongside family medical leave.
EvolutionIQ Insights
What We Do
EvolutionIQ's groundbreaking AI-powered claims guidance platform helps claims professionals balance timely, impactful actions and drive optimal claim resolutions. We simplify the claims process and distill complex medical information and insights. We enable claims professionals to focus on what matters most and handle claims with confidence and ease while delivering a personalized experience.
Why Work With Us
We're trailblazers reshaping the insurance claims industry and pushing the boundaries of what's possible. Join a workplace where innovation, fun, and growth go hand in hand. We champion internal promotions and continuous professional development. Collaborate with top minds, advance your career, and make a significant impact with us.
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