Top Machine Learning Jobs in Chennai

The Manager, Machine Learning will lead a specialized ML team at Databricks, managing hiring and developing customer relationships while overseeing key engagements. The role involves collaboration with R&D to influence product priorities, driving revenue and utilization, and embodying the company's cultural values.

As a Senior Software Engineer at ABBYY, you will drive the end-to-end development and delivery of scalable features and systems, ensure high standards of quality and performance, and collaborate with cross-functional teams. Your role includes monitoring system reliability, conducting code reviews, and continuously improving development processes while innovating with new technologies.

As a Senior Machine Learning Engineer at Atlassian, you will develop and implement cutting-edge machine learning algorithms, train complex models, and collaborate with teams to integrate AI features into Jira. Your role involves designing system architectures, conducting experiments, guiding junior engineers, and ensuring the practical application of AI within the product.

The Senior AI/ML Developer will design and implement machine learning applications, analyze large datasets, optimize algorithms, and collaborate with cross-functional teams to deliver impactful AI/ML solutions. Responsibilities include conducting experiments, improving model performance, and maintaining documentation for knowledge transfer.

The Machine Learning Engineer will develop and enhance telecom products, focusing on anomaly detection and forecasting. The role involves implementing ML Ops lifecycle, deploying models using TensorFlow and PyTorch, and managing data processing in distributed systems with PySpark and Kafka. The engineer will work closely with cross-functional teams and optimize algorithms through hyperparameter tuning.

The Sr Machine Learning Engineer will lead the development and enhancement of telecom AI products, implementing machine learning solutions for anomaly detection, forecasting, and fraud detection. Responsibilities include guiding teams, managing software updates, overseeing model deployment, conducting algorithm experimentation, and integrating systems into SaaS platforms.

As a Machine Learning Engineer, you will contribute to Global Regulatory Affairs by designing and implementing AI systems, developing decision support software, and collaborating on regulatory document enrichment using machine learning. You will also manage data and documentation systems to enhance efficiency and productivity within the team.

The Senior Staff ML Engineer will lead the implementation of ML infrastructure, mentor a team, collaborate with data scientists, establish best practices, architect deployment strategies, and optimize models for efficiency while integrating the latest technologies.

The Software Development Engineer (AI/ML) will develop and maintain sophisticated AI agents and generative AI applications, focusing on backend AI development. Responsibilities include designing scalable AI systems using Python, optimizing APIs for integration, managing data pipelines, and utilizing cloud technologies.

As a Machine Learning Engineer at Zuora, you will design and implement ML and AI-powered products, evaluate model performance, collaborate with teams to create end-to-end solutions, and establish best practices for AI governance. You will enhance product offerings through innovative machine learning features and maintain systems efficiency.

You will develop and evolve solutions using deep learning and AI frameworks, fine-tune LLM models, prototype solutions for ML and Applied AI, and preprocess big data for ML generation. Your role will also involve ensuring the observability and explainability of machine learning models.

The Vice President - Sr. AI/ML Data Science Engineer will lead the establishment and implementation of application systems, focusing on various machine learning libraries and big data technologies. They will collaborate with multiple management teams, handle data analysis, resolve complex business problems, and ensure application design meets architectural standards.

The Engineer 3, Machine Learning will focus on R&D in AI and ML, particularly in Generative AI. Responsibilities include developing solutions with deep learning, fine-tuning LLM models, preprocessing big data for ML generation, and enhancing ML observability and explainability.

The AI ML Engineering Manager will lead the team in developing Gen AI and ML solutions. Responsibilities include overseeing the design, development, and deployment of AI/ML models, managing a team, and collaborating effectively with cross-functional teams.

The role involves designing and developing machine learning software solutions for semiconductor metrology, collaborating with customers to define requirements, optimizing algorithms, extending prototypes into functional solutions, and maintaining software throughout its lifecycle. Documentation and technical support during testing phases are also key responsibilities.

The Engineer 3, Machine Learning role at Comcast involves developing solutions using deep learning and AI frameworks, fine-tuning LLM models, prototyping ML operations, preprocessing big data, and ensuring ML observability. Ideal candidates should have a passion for AI and an innovative mindset.

The ML Ops Engineer will develop and enhance telecom AI products, implementing robust machine learning models and algorithms. Responsibilities include managing the ML Ops lifecycle, deploying models in a cloud environment, conducting data analysis, and optimizing model performance. The role also emphasizes cross-functional collaboration and an understanding of telecom systems.