Machine Learning Engineer

RESPONSIBILITIES:
Kforce has a client in Austin, TX that is seeking a Machine Learning Engineer that will lead the development of end-to-end ML solutions to address complex and ambiguous business challenges. This job is located in Austin and requires Monday-Friday onsite and is a 6+ month contract to hire.

Overview:
This role involves designing and implementing scalable ML pipelines using frameworks like PyTorch and TensorFlow, working with multimodal datasets (e.g., images, voice, text, sensor data), and deploying models into production environments. The Engineer will collaborate cross-functionally with operations, quality, and controls teams to integrate ML solutions into existing workflows, ensuring performance optimization through techniques such as quantization and pruning. The role also emphasizes writing clean, maintainable code and establishing robust monitoring systems for deployed models.

REQUIREMENTS:
* A strong foundation in mathematics and statistics is essential, along with expertise in domains such as computer vision, NLP, or recommender systems
* Algorithm Development & Optimization: Rapid prototyping and refinement of ML algorithms with a focus on speed, scalability, and efficiency in real-world deployments
* Programming & System Integration: Advanced Python expertise for data processing, model development, and automation; Proficiency in C++ is highly desirable for integration with embedded systems and vehicle firmware
* Mathematical & Statistical Foundations: Strong theoretical background in Linear Algebra & Geometry; Probability Theory Numerical Optimization; Statistics for model evaluation and performance tuning
* Deep Learning Frameworks: Hands-on experience with PyTorch and TensorFlow for building and deploying ML models
* Model Optimization & Deployment: Skilled in techniques such as quantization, pruning, and TensorRT conversion to enhance model performance; Able to deploy and maintain ML solutions in production
* Domain Expertise: Demonstrated proficiency in at least one specialized area: Computer Vision; Large Language Models (LLMs); Recommender Systems; Operations Research
* Software Engineering Best Practices: Commitment to writing clean, modular, and maintainable code; Ability to translate research prototypes into robust, production-ready systems

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.