Solving real problems using state-of-the-art models and continually improving them through retraining, hyperparameter tuning, and architectural refinements at Slalom
Requirements
- Extensive experience using computer vision, deep learning, reinforcement learning, or natural language processing in production settings
- Strong foundation in algorithms, data structures, and object-oriented programming
- Deep proficiency with Python, and strong experience in frameworks like TensorFlow or PyTorch
- Experience with cloud platforms (AWS / GCP etc.)
- Model deployment, evaluation frameworks, and agentic system design
- Graduate-level work or specialization in ML or AI
Responsibilities
- Take state-of-the-art models (both proprietary and open source), put them into production to solve real problems, and continually improve them through retraining, hyperparameter tuning, and architectural refinements
- Collaborate with research and product teams to prototype and deliver enhancements that push what’s possible in ML applications — especially around agent frameworks, retrieval pipelines, and production APIs
- Work with large, diverse datasets to build both general-purpose and task-specific models
- Create and maintain scalable ML infrastructure to automate and optimize model development, training, deployment, and monitoring
- Serve as a technical advocate for ML techniques across engineering and product teams, raising the bar for quality and innovation
- Be adaptable: learn new technologies quickly and juggle multiple priorities in a fast-paced setting
Other
- Active [Level - Top Secret, Secret, etc] security clearance
- Meaningful time off and paid holidays, parental leave, 401(k) with a match
- A range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, and short/long-term disability
- Yearly $350 reimbursement account for any well-being-related expenses, as well as discounted home, auto, and pet insurance
- Equal opportunity employer and is committed to attracting, developing and retaining highly qualified talent
