Top Machine Learning Jobs in Huntsville, AL

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

As an ML Platform Engineer, you will enhance the core ML platform's performance and scalability, enabling faster innovation and impactful machine learning solutions.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

This role involves designing and implementing document intelligence workflows using large language models (LLMs), focusing on automation in financial technology products, and providing mentorship to team members.

The role involves designing and deploying a data lakehouse infrastructure, building ML pipelines, monitoring services, and collaborating with teams to optimize AI systems.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Work on Wayfinding projects using LLMs and agentic workflows, collaborate with engineering/product/research teams, receive mentorship, and gain hands-on experience with model evaluation, prompt engineering, and shipping code in a real engineering environment.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Senior ML Engineer on the Vision team responsible for framing ML problems, improving data acquisition and training pipelines, designing experiments, addressing model drift, building monitoring/visualization tools, collaborating across teams, and reviewing ML engineers' code to deploy robust models.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

Own productionalization of ML prototypes: deploy, monitor, and maintain scalable, reliable ML services for campaign optimization. Improve model quality, latency, observability, testing loops, data freshness, and rollout safety while sharing on-call responsibility.

The Senior Software Engineer II at Aledade will develop scalable AI/ML solutions, mentor junior engineers, and collaborate with cross-functional teams in the healthcare industry.