Artificial Intelligence & Machine Learning Engineer (Senior Consultant)

Fearless

3d•$120,588 - $195,955•Remote

About The Position

At Fearless, this Artificial Intelligence & Machine Learning Engineer (Senior Consultant) collaborates with cross-functional teams to align the technical vision, implementation, and quality of software systems across development, reliability, testing, and operations. This role will possess the skills to bridge business objectives with technical execution across software development, infrastructure, security, and testing at an advanced application-level of proficiency. The Sr. Consultant role will work on projects to ensure scalable, secure, and reliable solutions, while mentoring engineers, fostering collaboration, and aligning stakeholders with product and project goals. The Impact You Will Create: This project delivers high-performance AI and data solutions that enable federal civilian agencies to manage and analyze massive datasets in support of people-centered policy and decision-making. By implementing advanced AI agents and scalable cloud-based data pipelines, the effort translates complex AI capabilities into reliable, mission-driven outcomes at the speed and scale required for high-priority government initiatives.

Requirements

Analytical Thinking: The ability to observe and interpret information, break down complex problems into parts, identify patterns/relationships and draw logical conclusions to develop effective solutions.
Synthetic Thinking: The ability to combine different ideas, information, or concepts to create a new, complex understanding or solution by integrating disparate elements into a new, meaningful whole.
Adaptability: Comfort with change, flexibility in the face of shifting demands and resilience to setbacks.
Ownership & Accountability: Committed to taking responsibility for outcomes, ensuring that all commitments are met with a focus on enhancing service delivery.
Consultative Advising: Identifies and articulates client challenges, scopes projects and aligns recommendations to business goals and client expectations.
Communicating with Influence: Capable of crafting and delivering clear, persuasive messages that integrate data insights and structured narratives, tailored to the strategic needs of diverse audiences to drive effective decision-making.
Managing Priorities & Client Alignment: Skillfully negotiates and manages conflicting priorities to strategically align decisions, enhancing service delivery and client satisfaction.
Three (3) or more years of related experience
Ability to obtain and maintain a public trust clearance
AI/ML engineering with experience implementing Retrieval-Augmented Generation (RAG) and AI agents
Model fine-tuning expertise (e.g., RAFT or comparable techniques)
Strong programming skills in Python and Go
Large-scale data pipeline design and high-performance data processing
Experience working with massive datasets in production environments
Cloud platforms: Databricks and/or AWS
ML lifecycle management and CI/CD using tools such as MLflow
Ability to translate complex AI and data concepts into actionable solutions for non-technical stakeholders
Ability to sit for extended periods while working on a computer or during meetings.
Must be able to travel occasionally to client sites or company meetings.
Ability to communicate effectively via phone, email, and in-person, requiring clear speech, listening, and written communication skills.
Ability to move within an office environment, including reaching for files, using office equipment, and occasional light lifting (up to 10 pounds).

Responsibilities

Design, implement, and support AI-driven solutions for high-priority federal civilian government initiatives, focused on improving data accessibility, analysis, and policy outcomes.
Develop and configure AI agents using Retrieval-Augmented Generation (RAG) architectures to enable accurate, scalable, and explainable AI capabilities.
Fine-tune and optimize AI/ML models, with preference for experience leveraging RAFT or similar advanced fine-tuning techniques.
Build, maintain, and optimize large-scale data pipelines and data processing systems using Go, ensuring high performance, reliability, and scalability in data-intensive environments.
Collaborate with cross-functional teams to manage and process massive datasets that support analytics, AI models, and downstream applications.
Serve as a technical bridge between AI capabilities and stakeholder needs by translating complex technical concepts into clear, actionable solutions for non-technical and policy-focused audiences.
Partner with government stakeholders to understand mission goals and guide the practical application of AI and data solutions.
Leverage cloud-based platforms such as Databricks and/or AWS to support data engineering, model training, and deployment workflows.
Support ML lifecycle management and CI/CD processes for models, including experiment tracking and versioning using tools such as MLflow.