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.

Responsibilities

• Contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies.
• Provide high impact solutions on various projects including alpha research, portfolio construction, and risk management.
• Build high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
• 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.
• Operationalize machine learning models on AWS, including training, deployment, model registry, monitoring, and fine-tuning foundation models.
• Lead the implementation of a research project through the entire software development lifecycle using a full-stack implementation.
• Aid Research teams in developing new models and products that will provide an advantage to the organization in the marketplace.

Requirements

• 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.

Qualifications

• 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).
• 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; 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; Creative problem solver and a curiosity fueled by keeping up with advanced methodologies and industry trends, especially in the finance community.

Skills

• 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).
• 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; 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; Creative problem solver and a curiosity fueled by keeping up with advanced methodologies and industry trends, especially in the finance community.

Benefits

The base salary range for this position is $107,000-216,000 USD per year. Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors. Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

Pay

The base salary range for this position is $107,000-216,000 USD per year.

Schedule

Fidelity’s Onsite Working Model: Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Company

Fidelity will not provide immigration sponsorship for this position.