Machine Learning Engineer, Data Scientist

This is a fully remote position, open to applicants in Arizona, +15 more states.

📋 Description

• Design, create, and implement machine learning solutions that encompass a range of applications from traditional ML techniques (classification, clustering, recommendations) to LLM-based systems, including document parsing, data extraction, RAG pipelines, and LLM agents.

• Write clean, maintainable, and production-ready Python code that integrates seamlessly with the existing engineering and deployment frameworks.

• Handle large datasets to clean, preprocess, and analyze data while ensuring data quality and integrity.

• Apply and refine algorithms using industry best practices in machine learning, deep learning, and statistical analysis.

• Collaborate with business stakeholders to comprehend requirements and deliver data-driven solutions that yield actionable insights.

• Develop and sustain scalable pipelines and infrastructure for data processing, model training, versioning, deployment, and monitoring.

• Assess the performance of machine learning models, including LLM-specific evaluation methodologies, and fine-tune models for optimal results.

• Present findings, insights, and model performance to both technical and non-technical audiences.

• Keep abreast of the latest trends, technologies, and best practices in the field.

⛳️ Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related discipline.

• Bachelor's degree with 5+ years of relevant experience.

• Master's degree or higher with 3+ years of relevant experience.

• Proficient in Python with at least 3 years of coding experience.

• Strong software development practices in Python, including the ability to write maintainable, testable, and production-ready code.

• Solid understanding of LLM architectures and Generative AI.

• Practical experience in building and evaluating RAG pipelines.

• Familiarity with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, or similar).

• Proficiency in machine learning libraries such as Scikit-learn and PyTorch, along with fundamental libraries like NumPy and Pandas.

• Familiar with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker).

• Strong comprehension of model evaluation metrics across traditional ML (e.g., accuracy, precision, recall, F1) and LLM-based systems (e.g., faithfulness, answer relevancy, hallucination detection).

• Experience with model management tools such as MLFlow and the model development life cycle.

• Familiarity with version control tools such as Git.

• Proficient in adapting SDLC best practices for code development and testing.

• Exceptional problem-solving skills, analytical thinking, and the ability to thrive in a fast-paced environment.

• Strong communication skills with the capacity to explain complex technical concepts to non-technical stakeholders.

🏝️ Benefits

• 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.