Acuity is looking for a Data Scientist to join our Data Engineering Team. In this position, you will pioneer cloud and data services with our clients to deliver exciting IT & data driven capabilities. Research, prototype and deploy data products using the modernized platform that will integrate the latest advances in data engineering, visualization, Artificial Intelligence and Machine Learning.

Acuity is focused on building cutting edge, functional applications for government agencies. We are a team of doers with a bias towards action and have a proven track record of implementing innovative technology solutions to solve complex challenges. We're looking for a Lead User Experience (UX) Designer to join our team to help drive the design of premier product experiences for a suite of products. You'll work across multiple product teams to deliver innovative experiences that our customer relies upon. You'll nurture and guide a product design team, help shape the design vision and the strategic direction and play a key role at a formative stage in the team's next level of growth.

• As a Data Scientist / ML Engineer, you will be the trusted technical ML expert and work with our data engineering team to architect production-grade ML applications on Databricks. You will continue to strengthen your technical skills by applying the latest technologies in GenAI, MLOps, and ML, while expanding your impact through mentorship and establishing yourself as a ML expert.
• Architect production level ML workloads including end-to-end ML pipelines, training/inference optimization, integration with cloud-native services and MLOps
• Provide advanced technical support to our data engineering team from feature engineering, training, tracking, serving to model monitoring.
• Collaborate with our data engineering team to represent the voice of the customer, define priorities, and influence the product roadmap, helping with the adoption of Databricks ML offerings.
• Build and increase customer data science workloads and apply the best MLOps to productionize these workloads.