Top Machine Learning Jobs in Atlanta, GA

The Staff Software Engineer in Machine Learning at Headspace will lead the development of the ML Platform, driving the design and evolution of systems that enhance the capabilities of ML engineers. This role focuses on building scalable ML systems, automating model lifecycle management, engaging in collaborative problem-solving, and maintaining high engineering standards through technical leadership and mentorship.

As a Machine Learning Engineer, you will design and develop machine learning pipelines, optimize decision-making processes, and create pricing solutions for a two-sided marketplace in logistics. Collaborating cross-functionally, you will enhance automated systems and advocate for data-driven decisions.

The Technical Product Manager will collaborate with data science and engineering teams to optimize ad performance and user acquisition through advanced models and infrastructure integration. They will ensure effective communication with stakeholders and utilize data-driven insights to guide product success, while staying informed on industry trends and performance metrics.

The Senior Big Data Hadoop ML Engineer will develop and maintain scalable batch processing systems primarily using the Apache Hadoop ecosystem, implement CI/CD best practices, and manage Machine Learning workloads on GCP.

The Senior Principal AI/ML Engineer will lead the development of machine learning and generative AI solutions. Responsibilities include mentoring teams, collaborating with stakeholders, and driving innovation in analytics and ML applications that impact business decisions.

The Software Engineer (ML) at Tavus will develop features utilizing computer vision and NLP, manage ML Ops tasks such as testing and data processing, and improve generative AI models. The role requires ownership of technical direction and collaboration to enhance the company’s AI capabilities.

As a Staff Machine Learning Engineer at KUNGFU.AI, you will design and develop machine learning models, lead project teams, make architectural decisions, and collaborate with clients to deliver AI solutions that drive business value. You will also ensure continuous improvement and mentor other engineers.

The Senior Manager of AI/ML Engineering at Nike is responsible for leading teams of engineers and data scientists to deliver scalable AI/ML solutions, drive innovation, and enhance engineering best practices. This role involves mentoring staff, aligning efforts across teams, and staying updated on industry trends.

The Senior Software Engineer will scale machine learning for autonomous driving, collaborating with experts to build large-scale robotics systems, architecting and implementing solutions, and developing production-quality software within a strong safety culture. Responsibilities include building and optimizing machine learning training pipelines and cloud services.

As an AI / ML Developer at DuploCloud, you will design, develop, and optimize machine learning models while collaborating with internal teams and customers. You will be responsible for data preprocessing, deploying models in production, and ensuring their performance. Staying updated on AI advancements and conducting experiments will also be key aspects of your role, aimed at contributing to the company's growth.

The ML/AI Engineer at Yahoo Search will tackle real-world technical challenges by applying machine learning paradigms to develop scalable ML-based solutions. Responsibilities include data analysis, defining technical requirements, cross-functional communication, and staying updated on AI advancements. The role emphasizes quality, innovation, and effective solutions.

As a Senior Machine Learning Engineer at Concurrency, you'll design and engineer ML systems, collaborating with data science teams to solve diverse customer problems. You'll leverage your expertise in supervised, unsupervised, and deep learning, using tools like Python and SQL, while influencing project direction and designing production solutions in a cloud development environment.

The Machine Learning Engineer will utilize machine learning techniques to develop scalable solutions that enhance customer experience. Responsibilities include data analysis, implementing ML algorithms, automating processes, and general performance analysis.

The role involves designing, developing, and implementing software solutions for AI/ML projects, collaborating with teams, and utilizing various programming languages and cloud services. The developer will engage in agile practices, address technical challenges, and work with databases and APIs.

The Applied Scientist will apply advancements in AI technologies such as LLMs, CV, and NLP within the estate planning sector. Responsibilities include fine-tuning and integrating AI models, building Q&A frameworks, and collaborating with engineers to enhance AI quality in production systems.

As an ML Ops Engineer, you will set up and support ML bot inference, build scalable clusters, establish CI/CD for ML solutions, and improve inference logic for machine learning tasks.

The Senior AI/ML Engineer will design, build, and deploy AI/ML models to improve healthcare outcomes for low-income populations. The role involves collaborating with a multidisciplinary team to analyze patient data and develop intelligent systems, ensuring the solutions are scalable and aligned with the organization’s mission of health equity.