About The One Percent Athlete

The One Percent Athlete is an AI-native platform designed to revolutionize athlete development by integrating performance tracking, financial literacy, NIL deal management, and personal branding. Our mission is to help athletes maximize their potential both on and off the field by providing personalized growth pathways through AI-driven insights.

As an ML Engineer, you will be instrumental in developing and deploying AI systems, including LLMs, that power personalized recommendations for athletes. You will build real-time, data-driven insights to track progress, suggest training optimizations, and help athletes capitalize on financial and branding opportunities.

Key Responsibilities:

As a Machine Learning Engineer, you will:

Design, develop, and implement machine learning models leveraging large language models (LLMs) to provide personalized insights for athletes, including real-time performance feedback, financial literacy, and NIL guidance.
Work with Pinecone, LangChain, and other vector databases to efficiently store, retrieve, and use unstructured data, enhancing personalized recommendations and longitudinal tracking.
Integrate LLMs with LangChain to enable natural language-based interactions and recommendations on the platform, such as answering athlete queries and generating personalized training plans.
Develop and fine-tune LLM applications to ensure accuracy, relevancy, and scalability of personalized AI-driven content.
Collaborate with cross-functional teams (developers, data scientists, product managers) to deploy and optimize machine learning models, including LLMs, in a scalable cloud-based platform.
Implement natural language processing (NLP) pipelines for athlete communication tools, press conference training, and brand-building simulations.
Optimize data pipelines and model performance, ensuring high efficiency in retrieving and analyzing athlete performance metrics and social media engagement.
Deploy and manage ML models on cloud platforms such as Google Cloud or AWS for scalability and reliability.

Required Skills and Qualifications:

Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
1+ years of experience building and deploying machine learning models, particularly with LLMs (e.g., GPT, BERT) for applications like recommendation systems and NLP tasks.
Hands-on experience with Pinecone, LangChain, and vector databases for efficient data retrieval and semantic search.
Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and experience fine-tuning pre-trained LLMs.
Experience with cloud platforms like AWS, Google Cloud, or Azure, and proficiency in cloud-based ML tools (e.g., SageMaker, Vertex AI).
Proficiency in SQL and experience with databases such as PostgreSQL.
Experience with data pipelines, ETL processes, and handling unstructured data at scale.
Understanding of sports performance metrics, financial modeling, or athlete development is a plus.
Excellent problem-solving skills with the ability to work independently and creatively.
Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Nice-to-Have Skills:

Experience with natural language processing (NLP) for media training and athlete communication.
Familiarity with LLMs for conversational AI, personal branding, and NIL management.
Experience with Pinecone, LangChain, and using LLMs for real-time decision-making and recommendations.
Experience with AI-driven financial planning tools or performance tracking systems.

What We Offer:

A dynamic and innovative work environment that focuses on cutting-edge AI solutions in sports and athlete development.
Opportunities to work with advanced AI technologies like LLMs, Pinecone, and LangChain in building revolutionary athlete platforms.
Remote work flexibility with part-time or full-time opportunities.
Collaboration with industry leaders in technology, sports, and performance tracking.

Competitive compensation and significant opportunities for professional growth as we scale.

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Machine Learning Engineer