Machine Learning Team Lead
TackleAI, LLC in Schaumburg, IL seeks Machine Learning Team Lead. Design and
implement machine learning pipelines using Python, TensorFlow, and PyTorch, among other
tools. Understand business operations and train Artificial Intelligence (AI) models to achieve
business goals with accuracy and speed. Work with a vast array of development, inference,
and training servers that are crucial to the operation of the business. Research and apply
state-of-the-art machine learning techniques to solve real-world problems. Evaluate and
optimize the performance and scalability of machine learning models and systems. Build end-
to-end machine learning pipelines, including data ingestion, pre-processing, feature
engineering, model training, validation, and deployment. Conduct experiments and perform
statistical analysis to evaluate model performance and identify areas for improvement.
Document and communicate work and results to stakeholders and peers. Test, debug, and
monitor the performance and reliability of the AI systems and applications. Part-time
telecommuting is permitted within commutable distance to the office.
Must possess a Bachelor’s Degree in Computer Science, Engineering, Data Analytics,
Mathematics, or a related field and 3 years of experience in a Machine Learning Engineer
role. Must also possess experience with (i) collaborating with leadership to plan projects,
focusing on strategic goals and timelines; (ii) technical expertise with Nvidia Triton for model
server hosting and scaling; (iii) testing and evaluating new large language models (LLMs) and
their architecture and potential; (iv) innovating with LLMs such as implementing vector
databases and similarity search algorithms tailored for LLMs for AI research; (v) project
management including scoping out projects and ensuring they align with company goals; (vi)
balancing technical challenges with project delivery requirements; (vii) Machine Learning
including training and developing computer vision and NLP models; (viii) Infrastructure
Management: load balancing servers and deployment, focusing on ML Ops principles; (ix)
data cleaning, EDA, and generating synthetic or augmenting data to enhance model
performance; (x) Cloud and On-Premise Solutions such as utilizing AWS services, specifically
S3 and ECR, for cloud-based solutions; (xi) optimizing models for GPU performance on-
premises servers; (xii) Containerization and Orchestration: Docker and Docker Compose for
container orchestration for seamless development and deployment workflows; (xiii)
Programming and Development: TensorFlow, Keras, PyTorch, HuggingFace, SpaCy, and
MMocr for model development and implementation; (xiv) writing and serving gRPC and REST
APIs; and (xv) Integration and Deployment to enable full CI/CD pipelines, ensuring efficient
development, testing, and deployment cycles. Salary: $145,000 - $155,000 annually.