JOB SUMMARYWe are seeking a highly skilled and motivated
Machine Learning Engineer to join our growing Data Science team. You will develop and deploy cutting-edge machine learning models and advanced data analytics solutions to solve real-world problems. You will collaborate with cross-functional teams (Product, Data Platform, DevOps, Software Engineering, etc.) to extract meaningful insights from data, develop scalable machine learning solutions, and help drive data-informed decision-making.
PRIMARY ACCOUNTABILITIES- Design, develop, and deploy ML solutions ranging from traditional ML applications (classification, clustering, recommendations) to LLM-based systems, including document parsing, data extraction, RAG pipelines, and LLM agents.
- Write clean, maintainable, production-quality Python code that integrates smoothly with existing engineering and deployment infrastructure.
- Work with large datasets to clean, preprocess, and analyze data, ensuring data quality and integrity.
- Implement and optimize algorithms using best practices in machine learning, deep learning, and statistical analysis.
- Collaborate with business stakeholders to understand requirements and deliver data-driven solutions that provide actionable insights.
- Develop and maintain scalable pipelines and infrastructure for data processing and model training, versioning, deployment, and monitoring.
- Evaluate the performance of machine learning models, including LLM-specific evaluation approaches, and tune models for optimal performance.
- Communicate findings, insights, and model performance to both technical and non-technical audiences.
- Continuously stay updated on the latest trends, technologies, and best practices
KNOWLEDGE, SKILLS AND ABILITIES Minimum Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. or related experience.
- Bachelor with 5+ years of relevant experience
- Master or higher with 3+ years of relevant experience
- Fluent in Python (3+ years of coding experience)
- Strong software development practices in Python, including writing maintainable, testable, production-ready code.
- Solid understanding of LLM architectures and Generative AI.
- Hands-on experience building and evaluating RAG pipelines.
- Experience with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)Proficiency in machine learning libraries such as Scikit-learn and PyTorch; and fundamental libraries such as NumPy and Pandas
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker).
- Strong understanding of model evaluation metrics across traditional ML (e.g., accuracy, precision, recall, F1) and LLM-based systems (e.g., faithfulness, answer relevancy, hallucination detection), including approaches for evaluating non-deterministic outputs.
- Experience with model management tools such as MLFlow and the model development life cycle.
- Experience with version control tools such as Git.
- Proficiency in adapting SDLC best practices for code development and testing.
- Excellent problem-solving skills, analytical thinking, and the ability to work in a fast-paced environment.
- Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Behavioral
- Collaborator: work effectively with others, including domain experts, engineers, and business stakeholders
- Inquisitive: desire to ask questions and get a deeper understanding of issues
- Innovative: ability to imagine new analytical solutions to any problem
- Confident: able to challenge perceptions and biases of individuals at every level of the organization.
- Curious: stays abreast of current and upcoming technologies and tools
- Business-oriented: solid understanding of business requirements and vernacular
Preferred Qualifications
- Familiarity with optimizing, deploying and scaling automated training pipelines of transformer-based models.
- Familiarity with distributed training techniques and GPU-accelerated computing.
- Familiarity with classical NLP approaches.
- Experience implementing CI/CD pipelines for ML models for automating training, validation, monitoring, and scalable deployment.
- Experience with integrating and deploying AWS AI/ML services.
- Experience with Databricks
- Experience in Health Care data
SALARY, BENEFITS AND PERKS - Competitive total compensation package
- Medical and dental coverage at no premium cost for employees
- 401(k) and profit-sharing retirement plans
- Flexible spending accounts
- Paid time off (PTO)
- Company-paid holidays
- Gender-neutral parental leave
- Bereavement and pet leave
- Continuing education and professional accreditation sponsorship
- Life and AD&D insurance
- Short- and long-term disability
- Employee assistance program
- Mental health support program
- Additional perks
WORK ENVIRONMENTThis is a remote role; however, we only operate in the following states: AZ, CA, CO, FL, GA, IL, IN, MA, MI, MN, MO, NJ, NY, NC, OH, PA, TX and WI.Reflected below is the base salary range offered for this position. Actual salaries may vary depending on factors including but not limited to academic achievements, skills and experience. The range listed is just one component of the compensation package offered to candidates.
