Senior AI/ML Software Engineer (LLMs) at EvolutionIQ

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Apr, 26

Salary

225000.0

Posted On

13 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Python, Large Language Models, Statistical Machine Learning, Retrieval-Augmented Generation, Embeddings-Based Models, API Services, Prompt Engineering, Fine-Tuning, Collaboration, Model Evaluation, Hybrid Approaches, Scalability, Performance Optimization, Clean Code, Medical Document Processing, Human-in-the-Loop Workflows

Industry

Software Development

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! The Adventure: We're the leading AI Guidance Platform in the insurance industry today, working with some of the largest insurance carriers in the US and expanding globally. We are growing incredibly fast and have a nearly 100% success record in converting pilots to production deployments. You will be designing on a shared, unified platform that can scale across multiple lines of business. Our engineering culture values simplicity, core engineering principles, quality, honesty, transparency and strong collaboration. If you’re excited to work on a fast-moving enterprise engineering team using the latest technologies at high scale, we want to meet you. About You: As an ambitious AI/LLM 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 driving projects end-to-end, from ideation through deployment. 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: 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 with Product teams to rapidly iterate on feedback and deliver impactful features 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: 3+ 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 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 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) Work-life, Culture & Perks: Compensation: The base salary range is $175-225K, 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.

Responsibilities

You will design, build, and deploy AI-powered features for the claims synthesis product, focusing on extracting information from medical documents. Additionally, you will collaborate with teams to improve model performance and translate AI research into production solutions.