Principal Quant Developer (MLOps)

About the role

The Quantitative Research & Investing Technology (QRIT) team within Fidelity's Asset Management Technology group is seeking a highly motivated and curious Principal Quantitative Developer. In this role you will contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies. You will provide high impact solutions on various projects including alpha research, portfolio construction, and risk management. Your technology knowledge covers a broad spectrum of technologies, including R, Python, and PL/SQL databases, positioning you as a full-stack software engineer who capitalizes on enterprise technology. You are committed to constructing high-quality, scalable, robust, resilient and efficient analytical and software solutions that propel investment processes forward. You will possess: A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role. Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role. This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques. The Expertise and Skills You Bring Core Engineering Expert in Python with experience across the development stack (full stack) Exposure to object-oriented programming (OOP) and design patterns Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability Data & Infrastructure Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask) Proven ability to construct and manage robust data pipelines and event-driven workflows Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2 DevOps & CI/CD Experience in containerization with Docker and orchestration with Kubernetes Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management MLOps & AI Infrastructure Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning) Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models Familiarity with experiment tracking and model versioning tools (e.g., MLflow) Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics Awareness of responsible AI governance practices Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset Quantitative & Domain Knowledge Demonstrated knowledge of mathematics, statistics, and quantitative finance Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms Domain knowledge in either equities, fixed income or alternative asset classes Progress towards CFA (or equivalent) a plus Collaboration & Communication Strong presentation and communication skills, with a knack for engaging with quant researchers and investment professionals Strong problem-solving skills, with a proven ability to work effectively in cross-functional teams A creative problem solver and a curiosity fueled by keeping up with advanced methodologies and industry trends, especially in the finance community Lead the implementation of a research project through the entire software development lifecycle using a full-stack implementation Assist Research teams in developing new models and products that will provide an advantage to the organization in the marketplace Demonstrates eagerness and aptitude for rapidly a

Additional Information

Job Description: Note: Fidelity will not provide immigration sponsorship for this position.

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