Top Machine Learning Jobs in Pune

The Implementation Lead will manage customer implementations of Lyric's AI-powered platform, ensuring projects meet timelines, success criteria, and technical quality while collaborating across teams.

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.

Lead AI/ML projects, design Generative AI models, create agent AI architectures, build LLM applications, and collaborate on AI solutions for real-world applications.

Lead technical design and architecture strategy for high-value digital solutions sales, collaborating with sales teams to present solutions and ensuring technical integrity during proposals.

The Senior Backend Engineer will design, develop, and maintain software solutions for identity verification, focusing on scalability, security, and high performance, while mentoring junior engineers and collaborating in an agile environment.

The role involves designing and implementing machine learning models, conducting data analysis, and collaborating with teams to develop AI solutions for supply chain optimization and decision-making.

As a Backend Engineer at Socure, you'll design, develop, and deploy software solutions, ensuring scalability, security, and high quality while mentoring junior engineers and collaborating in an agile environment.

The intern will engage in full-stack development, collaborating with teams, optimizing code, and exploring AI techniques, while learning Agile methodologies.

As a Customer Facing Data Scientist, you'll support customers through pre-sales and ongoing engagements, leveraging AI and data science to solve complex problems, collaborate with various stakeholders, and present at conferences.

The Senior Technical Program Manager will drive enterprise-level Data, AI, and ML initiatives, ensuring successful product roll-out and technology adoption while managing scope and aligning with business priorities.

The Data Scientist will analyze complex datasets, develop predictive models, and derive insights to support business objectives using advanced statistical methods.

The Senior AI/ML Engineer focuses on developing digital twin simulations and optimization models to enhance warehouse logistics and operational efficiency.

Develop customer-facing automation solutions, contributing to design, coding, and troubleshooting, while collaborating with stakeholders on technical issues.

Design and implement scalable distributed systems and ML services. Drive innovation in AI-driven network management and mentor junior engineers.

Lead the design, development, and implementation of AI-driven network solutions, guiding the full software development lifecycle and technical innovation.

Design and implement AI/ML solutions for workforce management, focusing on forecasting, scheduling, and LLM integration, while collaborating cross-functionally.

Join the AI Factory team to develop ML solutions that enhance patient care. Collaborate with cross-functional teams, mentor juniors, and innovate machine learning algorithms in a production environment.

Develop AI and ML models to enhance patient care, collaborate with cross-functional teams, mentor junior engineers, and explore new ML techniques.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

The AI/ML Engineer II role involves developing AI solutions, managing product backlogs, integrating LLMs, and collaborating on automation projects while leading improvements in IT processes.

The ServiceNow Solution Architect - AI leads a team to develop AI-driven applications on the ServiceNow platform, integrating ML and NLP solutions, and managing all development aspects from design to testing.

Lead the development of RCM workflows enhanced by AI, manage product roadmaps, prioritize backlogs, and collaborate with cross-functional teams.

The role involves designing, training, and deploying machine learning models, integrating LLMs, and implementing MLOps best practices. Collaboration with cross-functional teams is essential to drive AI initiatives.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

The role involves designing and implementing machine learning solutions, collaborating with stakeholders, overseeing project architecture, and applying AI ethics. Responsibilities include translating business needs into technical designs and mapping solutions effectively.