Top Machine Learning Jobs in Delhi
Join a company focused on delivering business benefits through AI/Machine Learning solutions. Responsibilities include identifying opportunities, prototyping, collaborating with BI & Analytics, conducting research experiments, and deploying end-to-end data science solutions with challenging datasets. Required skills: Python, ML tool kit, DL frameworks, ML deployment strategies, micro services, infrastructure.
Design, develop, and implement artificial intelligence (AI) solutions leveraging advanced algorithms and machine learning techniques. Collaborate with cross-functional teams to automate processes, improve decision-making, and drive innovation. Develop and optimize generative AI models, maintain AI pipelines, and provide technical mentorship to junior team members. Ensure fairness, transparency, and accountability in AI models and systems.
Seeking an Engineer III with expertise in ML Ops to design and build a modern ML-Ops platform, modularize ML code, establish repeatable patterns for model development, and leverage cloud services. This role involves collaborating with Data Platform Software Engineers, Data Scientists, and Threat Analysts to influence critical business decisions through scalable ML pipelines.
The Sr. Engineer - ML Ops at CrowdStrike will play a crucial role in building the ML Experimentation Platform and designing scalable ML pipelines. Responsibilities include modularizing ML code, establishing repeatable patterns for model development, and leveraging cloud services in a cloud-first environment.
Seeking a highly skilled Senior Machine Learning Engineer to lead the development of ML infrastructure, from model training to deployment. Responsibilities include implementing ML infrastructure, providing technical leadership, mentoring a team of engineers, collaborating with data scientists, and establishing best practices for model deployment.
Looking for a Machine Learning Engineer with 6+ years of experience in AI and Machine learning to build efficient, data-driven artificial intelligence systems. Responsibilities include designing, developing, testing, and deploying machine learning models, collaborating with cross-functional teams, optimizing model performance, and staying updated on the latest ML technologies.
Canonical is hiring an AI/ML and MLOps Field Engineer to help global companies embrace AI in their business using open source capabilities on public and private cloud infrastructure, Linux, and Kubernetes. The role involves working with enterprise customers to solve real-world problems and enable the adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC, and related technologies.
Collaborate with data scientists and machine learning engineers to build backend systems, design and implement APIs, optimize backend infrastructure, and maintain CI/CD pipelines for automated testing and deployment. Requires 5+ years of experience in commercial software development with strong analytical skills and familiarity with microservice architecture.
The ML Engineer will be responsible for conceptualizing, designing, and implementing ML models for dynamic pricing strategies and personalized product recommendations. They will work on data pipelines, develop and deploy machine learning models, and collaborate with cross-functional teams to align solutions with strategic objectives.
Seeking a highly skilled Senior Machine Learning Engineer to lead the development of ML infrastructure and collaborate with diverse teams to deliver impactful solutions. Responsible for architecting and deploying ML models, propelling products to new levels of success.
We are looking for a Rust Engineer to contribute to our groundbreaking Hiveon ASIC Firmware product, revolutionizing the world of ASICs with innovative and game-changing solutions of our firmware.
As a Software Engineer on our ML Product team, you will be responsible for defining and improving the workflow of our open-source machine learning tools. You will work closely with technical product managers and have hands-on experience in deep learning. Strong communication and software engineering skills are required.
As an Engineering Manager at Turing.com, you will lead a team of talented engineers, drive technical vision and execution of complex projects, and foster a culture of continuous improvement and excellence. Key responsibilities include leading innovation efforts, managing project allocation, optimizing development processes, and identifying high and low performers in teams. Requires strong leadership in Python with Python expertise and experience in Computer Vision (CV) as a plus.
Seeking a talented Senior Generative AI Engineer with experience in developing and training Generative AI models. Responsibilities include implementing advanced machine-learning algorithms and models to enhance the platform's capabilities. Must have proficiency in Python and hands-on experience with machine-learning models.
Lead the design and implementation of data architectures, develop data pipelines, manage databases, oversee data quality and governance, provide mentorship and leadership, collaborate with stakeholders, and monitor performance for a digital banking platform.
Develop and maintain the ASIC Hub application, ensuring seamless communication with devices within the local network. Implement robust TCP/UDP communication protocols to facilitate efficient data exchange. Design and write system monitoring solutions tailored to the unique requirements of the mining industry. Collaborate closely with a team of Go Engineers, sharing knowledge and expertise to drive the project forward. Engage in data-driven development, managing and optimizing the flow of large datasets.
Seeking a dynamic Recruiter with 4+ years of experience in in-house or consulting recruitment supporting diverse business needs. Responsibilities include talent acquisition, candidate relationship management, collaboration with hiring managers, job posting, interviewing and evaluation, and data management. Must have experience in Europe/UK hiring and strong communication skills.
Design and develop innovative ML-powered product capabilities, work through the entire feature lifecycle, collaborate with the team, and contribute to identifying and solving technical challenges around data streams.
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