Top Senior Machine Learning Jobs in Baton Rouge, LA

Develop AI/ML-powered features in ClickHouse Cloud, focusing on frontend and API architecture, UI/UX, and integrations with AI systems.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

Lead architecture and development of a SaaS platform for data center energy procurement. Build forecasting, contracting, and monitoring modules; implement AI tools on AWS (Bedrock, SageMaker); hire and mentor engineers; translate business logic into scalable systems; deliver demos to investors and customers.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The Director of AI & ML is responsible for establishing and leading the AI function, defining AI strategy, building a high-performing team, and delivering production-grade ML and AI solutions within healthcare payer workflows.

Lead design, build, and operation of end-to-end production ML systems (feature pipelines, training, inference, experimentation, monitoring) for ranking, recommendation, rewards, ROAS/LTV prediction, personalization, and offer optimization in a high-scale AdTech environment. Provide hands-on technical leadership, mentor engineers, drive MLOps and observability standards, and partner with Data Engineering, BI, Product, and business teams to connect models to outcomes.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

The Specialist Solutions Architect will guide customers in architecting ML & AI applications, provide advanced technical support, and collaborate cross-functionally to enhance Databricks' AI offerings.

Lead end-to-end ML system development: data exploration, model research, training, deployment, evaluation, and MLOps. Collaborate cross-functionally to prioritize claims, improve matching, measure business impact, and own a technical workstream.

Lead design, development, and production deployment of ML and generative AI solutions at scale. Drive personalization, pricing, experimentation, agentic AI, and simulation modeling. Partner with engineering and product teams, mentor engineers, influence technical strategy, and measure business impact through data-driven experimentation.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

Lead GoDaddy's three-year Generative AI and ML roadmap, architecting and scaling agentic and personalized AI solutions globally. Own end-to-end ML systems, enable rapid experimentation, ensure governance/compliance, and partner across product, engineering, and analytics. Mentor and grow high-performing teams and drive adoption of advanced AI techniques to improve customer experiences and business outcomes.

Lead development of internal Python SDKs and agentic AI workflows, build scalable FastAPI ML services, maintain CI/CD with Jenkins/GitLab Runners, and use Galileo for model evaluation and observability to productionize autonomous systems.

Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Lead program delivery for engineering teams at Arine, optimizing internal processes and ensuring timely execution of technical programs while facilitating Agile methodologies.

Lead design, development, and delivery of ML, DL, and Generative AI systems for production. Apply prescriptive analytics, optimization, recommendation, and reinforcement learning. Build and evaluate models, run experiments, develop prototypes, benchmark methods, and collaborate with business partners to translate data into actionable recommendations and influence strategy.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Develop and iterate deep learning models for protein-ligand co-folding and structure prediction, benchmark performance, integrate validated models into production drug-discovery pipelines, analyze structural and sequence data, communicate findings, and collaborate with multidisciplinary teams to scale research into products.