104 Ml Models Jobs

As a CDP Specialist, you will be responsible for building, optimizing, and managing a robust customer data ecosystem to support personalized marketing strategies, analytics, and data-driven decision-making. The role demands technical expertise and hands-on development skills to implement and maintain the CDP infrastructure. Lead the implementation and configuration of the Customer Data Platform, ensuring proper integration with marketing technologies. Oversee the collection, organization, and maintenance of customer data within the CDP, ensuring it is accurate, complete, and up to date. Implement data governance protocols to maintain data quality, consistency, and compliance with regulatory standards. Leverage the CDP to create highly targeted and segmented customer groups based on behaviors, demographics, and past interactions. Collaborate with marketing teams to ensure the effective use of customer segments for email, social, web, and other marketing channels. Use and implement ML models on the CDP platform to derive actionable insights from customer data stored in the CDP. Develop predictive analytics models to enhance customer segmentation, improve personalization strategies, and drive dynamic pricing models. Implement recommendations and personalization in marketing campaigns across email, social media, web, and app channels. Leverage powered tools to predict customer behaviors, optimize campaigns, and recommend relevant content or products to customers. Qualifications: Education: Bachelors degree in marketing, Data Science, Computer Science, Business Analytics, or a related field. A masters degree is a plus. Experience: 2-6 years of experience working with Customer Data Platforms, AI/ML-driven tools, and marketing technologies. Technical Skills: Proficiency in CDP platforms such as Adobe Experience Platform, or similar. Strong understanding of AI/ML algorithms, predictive analytics, and ML business models powered. Experience in tools like Python, R, or similar for AI model development.,

Location: Pune, Onsite(WFO) Department: Engineering / Data & AI Reports To: Associate Director of Engineering Job Summary We are seeking an Associate Machine Learning Engineer of exposure and experience in developing AI solutions, including Generative AI, classical ML models, and data engineering pipelines. You will play a hands-on role in building and deploying scalable ML and GenAI applications. Key Responsibilities - Generative AI Development - Design and implement applications using large language models (LLMs). - Optimize prompts using techniques such as Chain of Thought, Few-Shot Learning, and RAG. - Build scalable APIs and pipelines for GenAI-powered features. Machine Learning Engineering - Build and deploy ML models (classification, regression, recommendation, etc.). - Apply MLOps practices for model training, testing, deployment, and monitoring. Data Engineering - Build and maintain data pipelines using Python and cloud-native tools. - Ensure availability, scalability, and quality of data used in AI workflows. - Work closely with backend and other engineering teams to integrate data systems. Model Deployment & Maintenance - Deploy ML models via APIs, containers, or cloud services. - Monitor production models and optimize their performance and scalability. Qualifications Required: - Exposure GenAI and ML/AI projects would be plus . - Proficiency in Python and ML libraries (e.g., Hugging Face, LangChain, OpenAI). - Strong skills in building APIs and deploying AI solutions. - Experience in data pipeline development. Preferred: - Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). - Exposure to classical ML or DL in production. - Prior experience in early-stage/startup environments - Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). Understanding of cloud platforms (Azure preferred).

About Paytm Group: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm's mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the role : Are you someone who loves to build products and also gets curious about the technology stack being used Have you worked in technical roles at some point in your career and enjoyed them (be it software developer, engineering manager, or architect) We are looking for Product Owners to enable the delivery of high-quality financial/payment products in a fast-paced, challenging, and creative environment. You will work with business heads and engineering partners to drive the strategy, roadmap, execution of a product area to build high-quality products/systems. Expectation: . Working closely with business leads to understand product use cases, customer journeys, business applicability and impact of each use case. . Ability to understand different technology platforms, their features and be able to work with solution architects/engineering leads and write detailed product requirement documents, manage future roadmaps and deliverables. . Make sure that clear, simple, and technically sound decisions are made. . With your strong knowledge of different technology platforms in your vertical or in the company, we expect you to raise your hand when either any wrong design decision is being made or if similar function exists in other systems that could be reused. . Ability to work with multiple stakeholders / senior management / cross-functional teams to influence them for quicker decisions, manage sudden technical roadblocks and be able to clear them. . Lead product team processes (Agile/Scrum) and manage expectations and track roadmap regularly . Be involved in what your team is building - Run edge cases, test products proactively and its features to provide feedback early in the cycle, make sure entire journeys are covered, and that product reporting exists to track KPIs for the product and its success (data-driven product management). Superpowers that will help you succeed in this role: . Bachelors degree in engineering, computer science and/or related field . MBA from premier institution . Professional experience in a product management or analytical role, Exp should be in between 8-12 years, out of which minimum 6 years in product management . Experience in experience in building ML models+ recommendation engines would be a plus . Have an extreme bias towards action basically, you need to have the Get Shit Done attitude . Solutions orientated within a high-energy and fast-paced work environment . Exceptional customer experience intuition demonstrated success in creating innovative and user-friendly products and customer-facing features . Possess excellent oral, written, verbal and interpersonal communication skills Why join us . A collaborative output driven program that brings cohesiveness across businesses through technology . Improve the average revenue per use by increasing the cross-sell opportunities .A solid 360 feedback from your peer teams on your support of their goals . Respect, that is earned, not demanded from your peers and manager Compensation : If you are the right fit, we believe in creating wealth for you. With enviable 500 mn+ registered users, 17 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants - and we are committed to it. India's largest digital lending story is brewing here. It's your opportunity to be a part of the story!

About Cohyve Cohyve is an AI-powered design ecosystem that is revolutionizing how businesses access creative services. By integrating Creative Intelligence (CI), our proprietary AI-driven workflow automation, designer-business matching, and generative design tools, we are making high-quality design 10x faster, more scalable, and cost-efficient. We have early traction with soft commitments from 5+ companies, 25+ in the pipeline, and 400+ vetted designers onboarded. Now, we are looking for a Tech Co-founder who can lead our AI & product development while also investing in the company to drive growth and scalability. We are seeking a visionary Tech Co-founder who is passionate about AI, design-tech, and building scalable SaaS platforms. As a co-founder, you will play a key role in shaping Cohyve's technology roadmap, AI development, and overall product strategy. Must-Have Skills & Experience: - Strong expertise in AI/ML, full-stack development, and cloud infrastructure. - Experience with building and scaling AI-powered SaaS platforms (Generative AI, NLP, ML models, etc.). - Hands-on coding ability (Python, TensorFlow, PyTorch, AWS, React, Node.js, etc.). - Prior experience in leading tech teams or building a startup from the ground up. - Product-first mindset with a deep understanding of UX, design workflows, and automation. Bonus Points for: - Experience in computer vision, generative AI, or AI-driven creative tools. - Prior fundraising experience or investor network in SaaS/AI startups. - Background in startup accelerators, VCs, or successful exits. Role & Responsibilities - Lead Technology & AI Development: Architect and develop Cohyve's AI-powered design ecosystem. - Build & Scale the Product: Ensure seamless UX, automation, and high-performance infrastructure. - Grow & Manage the Tech Team: Hire and mentor engineers, AI specialists, and product developers. - Drive AI & Product Innovation: Enhance Creative Intelligence (CI) and automation tools. - Work Closely with the Founding Team: Define strategy, fundraising, and business growth. - Investment Commitment: Bring skin in the game with a financial contribution to accelerate growth & tech development. What's in It for You - Co-founder title & significant equity stake (Negotiable based on investment & expertise). - Build & own a game-changing AI-powered creative SaaS product. - Be part of a high-growth startup with global expansion potential. - Work alongside industry experts in design, AI, and business strategy. - Influence Cohyve's roadmap, from tech development to market expansion. How to Apply If you're an AI-driven tech leader who wants to build, invest, and scale an industry-defining startup, let's talk! DM or email rupesh@cohyve.in with your background, portfolio, and investment interest.,

Role: Machine Learning Engineer Exp: 3-8 years Notice period: Immediate Mode: Work from office(5 days) Location: Hyderabad Looking for a driven and innovative Machine Learning Engineer to help us scale and foresee problems that aren't apparent. We're seeking a hands-on individual with a strong passion for data and a proven ability to translate complex data challenges into robust, scalable machine learning solutions. In this role, you'll be a key player in developing, deploying, and maintaining ML models that directly impact our core business functions and enhance user experiences. If you thrive in a collaborative, fast-paced environment, excel at working with diverse data sources, and possess a solid foundation in machine learning principles and MLOps, we encourage you to apply. Key Responsibilities Design, develop, and implement end-to-end machine learning models, from initial data exploration and feature engineering to model deployment and monitoring in production environments. Build and optimize data pipelines for both structured and unstructured datasets, focusing on advanced data blending, transformation, and cleansing techniques to ensure data quality and readiness for modeling. Create, manage, and query complex databases, leveraging various data storage solutions to efficiently extract, transform, and load data for machine learning workflows. Collaborate closely with data scientists, software engineers, and product managers to translate business requirements into effective, scalable, and maintainable ML solutions. Implement and maintain robust MLOps practices, including version control, model monitoring, logging, and performance evaluation to ensure model reliability and drive continuous improvement. Research and experiment with new machine learning techniques, tools, and technologies to enhance our predictive capabilities and operational efficiency. Required Skills & Experience 3-8 years of hands-on experience in building, training, and deploying machine learning models in a professional, production-oriented setting. Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts. Proven expertise in data blending, transformation, and feature engineering , adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data. Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable. Proficiency in programming languages commonly used in data science (e.g., Python is preferred, R). Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like Deep Learning, Natural Language Processing (NLP), or Computer Vision . Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ). Familiarity with MLOps tools and practices , including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines. Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs. Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development. Educational Background Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, or a closely related quantitative field.

Job Title: Data Scientist ML, GenAI & Agentic AI Position Summary We are seeking a Data Scientist with a strong background in enterprise-scale machine learning , deep expertise in LLMs and Generative AI , and a clear understanding of the evolving Agentic AI ecosystem . The ideal candidate has hands-on experience developing predictive models, recommendation systems, and LLM-powered solutions, and is passionate about leveraging cutting-edge AI to solve complex enterprise challenges. This role will involve working closely with product, engineering, and business teams to design, build, and deploy impactful AI solutions that are both technically robust and business-aligned. Key Responsibilities ML & Predictive Systems Development Design, develop, and deploy enterprise-grade machine learning models for recommendations, predictions, and personalization use cases. Work on problems such as churn prediction, intelligent routing, anomaly detection, and behavior modeling. Leverage techniques in supervised, unsupervised, and reinforcement learning as needed based on business context. LLMs & Generative AI Build and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, or open-source models) for tasks such as summarization, semantic search, document understanding, and copilots. Deliver production-ready GenAI projects , applying techniques like RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning, and vector search (e.g., FAISS, Pinecone, Weaviate). Collaborate with engineering to embed LLM workflows into enterprise applications, ensuring scalability and performance. Agentic AI & Ecosystem Engagement Contribute thought leadership and experimentation around Agentic AI architectures , task orchestration, memory management, tool integration, and decision autonomy. Stay ahead of trends in the open-source and commercial LLM/AI space, including LangChain, AutoGen, DSPy, and ADK-based systems. Develop internal PoCs or evaluate frameworks to assess viability for enterprise use. Collaboration & Delivery Work with cross-functional teams to identify AI opportunities and define technical roadmaps. Translate business needs into data science problems, define success metrics, and communicate results to stakeholders. Ensure model governance, monitoring, and explainability for AI systems in production. Required Qualifications Master’s or PhD in Computer Science, Data Science, Statistics, or related field. 5–8 years of experience in data science and ML, with strong enterprise project delivery experience. Proven success in building and deploying ML models and recommendation systems at scale. 2+ projects delivered involving LLMs and Generative AI , with hands-on experience in one or more of: OpenAI, Hugging Face Transformers, LangChain, Vector DBs, or model fine-tuning. Advanced Python programming skills and experience with ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, TensorFlow). Experience with cloud-based ML/AI platforms (e.g., Vertex AI, AWS SageMaker, Azure ML). Strong understanding of system architecture, APIs, data pipelines, and model integration patterns. Preferred Qualifications Experience with Agentic AI frameworks and orchestration systems (LangChain, AutoGen, ADK, CrewAI). Familiarity with prompt optimization, tool chaining, task planning, and autonomous agents. Working knowledge of MLOps best practices including model versioning, CI/CD for ML, and model monitoring. Strong communication skills and ability to advocate for AI-driven solutions across technical and non-technical teams. Regular follower of AI research, open-source trends, and GenAI product developments.

Job Description: Join our core R D Automotive Engineering Team Infosys is hiring core Automotive R D professionals This is an opportunity to be part of cutting edge automotive software projects working with passionate global teams tackling real world Automotive and next generation Electric Mobility Challenges If such an opportunity excites you apply for the job opening below Key Responsibilities: A day in the life of an Infoscion As part of the Infosys consulting team your primary role would be to get to the heart of customer issues diagnose problem areas design innovative solutions and facilitate deployment resulting in client delight You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise You will plan the activities of configuration configure the product as per the design conduct conference room pilots and will assist in resolving any queries related to requirements and solution design You will conduct solution product demonstrations POC Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization s financial guidelines Actively lead small projects and contribute to unit level and organizational initiatives with an objective of providing high quality value adding solutions to customers If you think you fit right in to help our clients navigate their next in their digital transformation journey this is the place for you Technical Requirements: 5 years of working experience of in vehicle software development in Automotive OEMs or Tier 1 Suppliers Should have thorough knowledge of Automotive software development and validation Experience in leveraging AI including a Programming language like Python or Scala working with ML models and AI services on the cloud like AWS AI services Knowledge of DevOps tools and processes Preferred Skills: Domain->Automotive->Automotive - Systems,Technology->DevOps->DevOps Architecture Consultancy,Technology->Machine Learning->Responsible AI->ethical ai

You will be responsible for working on August's product features and applications. This role requires creative thinking, combined with a strong backend engineering and AI/ML skillset. Responsibilities Own the end-to-end build-out of features. Set up training and testing pipelines for language model systems. Create and maintain high-quality test cases and metrics to ensure a great product experience. Maintain and improve existing functionalities and features. You might be a good fit if you have: 5+ years of experience working with backend and frontend systems. Excitement to learn how LLMs can be used to build high-performing applications. Experience working with Python. Experience in training ML models and fine-tuning LLMs. Results-oriented mindset, with a bias towards flexibility and impact. Willingness to pick up slack, even if it goes outside your job description.,

You will be responsible for interacting with clients (internal or external) to understand their problems and develop solutions to meet their needs. You will lead projects and collaborate with a team to ensure that requirements are identified, user stories are created, and work is planned effectively to deliver solutions that align with evolving business needs. Managing team activities, strategizing task approaches, setting timelines, and delegating tasks among team members will be part of your role. You will conduct meetings, document findings, and communicate effectively with clients, management, and cross-functional teams. Additionally, you will create ad-hoc reports for internal requests and automate processes using data transformation tools. To excel in this role, you should possess strong analytical, problem-solving, interpersonal, and communication skills. Proficiency in DBMS, Data Modelling, and SQL querying is essential. Experience with cloud technologies (GCP/AWS/Azure/Snowflake), ETL/ELT pipelines, CI/CD, orchestration tools (e.g., Apache Airflow, GCP workflows), and Python for ETL/ELT processes and data modeling is required. You should also be adept at creating reports and dashboards using Power BI/Tableau and have knowledge of ML models and Gen AI for modern architectures. Experience with version control platforms like GitHub, IaC tools (e.g., Terraform, Ansible), stakeholder management, client communication, and Financial Services domain will be advantageous. Familiarity with Machine Learning tools and techniques is beneficial. Ideally, you should have 3-7 years of experience and hold a BTech/MTech/BE/ME/MBA in Analytics. Compensation will be in line with industry standards.,

Job Description: As a Senior MLOps Engineer, you will collaborate with other Engineers, Development teams, Product Owners & Scrum Masters to realize critical business goals and be part of a team of smart, highly skilled technologists who are passionate about learning, data mining and prototyping cutting-edge technologies. We develop RESTful API applications in Python and what we do is to help our research team to put ML models in production, so we work mostly in building Restful applications and training pipelines (mostly in AzureML), integrating inference codes, and providing tools and patterns for enhancing our MLOps cycle Responsibilities: Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to the user requests in near real time. Develop RESTful Applications using Python. Design and implement the pipelines for training and deployment of ML models. Design dashboards to monitor a system, collect metrics, create alerts based on them and execute performance tests. Perform feasibility studies/analysis with a critical point of view and support & maintain (troubleshoot issues with data and applications). Contribute to architectural designs of large complexity and size, potentially involving several distinct software components. Mentoring other engineers fostering good engineering practices across the department., Working closely with data scientists and a variety of end-users (across diverse cultures) to ensure technical compatibility and user satisfaction. Work as a member of a team, encouraging team building, motivation and cultivating effective team relations. Use distributed computing to validate and process large volumes of data to deliver insights. Evaluate technologies we can leverage, including open-source frameworks, libraries, and tools. Interface with product and other engineering teams on a regular cadence Develop technical documentation for applications, including sequence diagrams, flowcharts and manuals. Qualifications: 7+ years of applicable data engineering experience, including Python & RESTful APIs. Strong knowledge of data structures, algorithms and designing for performance, scalability and availability. Strong knowledge of pandas, numpy, flask & sqlalchemy python libraries. Strong fundamentals in data mining & data processing methodologies. Sound understanding of Big Data & RDBMS technologies, such as SQL, Hive, Spark, Databricks, Snowflake or Postgresql. Orchestration and messaging frameworks: Jenkins, Messaging queue frameworks (Kafka). Experience in Azure or any cloud computing. Experience and knowledge in Linux & container orchestrators (Kubernetes, Docker Swarm.) Experience in using collaborative developing tools such as Git, Confluence, Jira, etc. Excellent English communication skills, with the ability to effectively interface across cross-functional technology teams and the business. Minimum B.S. degree in Computer

Lead and direct a team to deliver annual objectives for the business and team using advanced analytics. Develop, mentor, and coach team members to ensure strong succession plans are in place and encourage empowerment and collegiality. Create a talent destination through branding, community, and academic partnerships. Conform to Barclays management processes and play a crucial role in project prioritization and planning. Be a key partner to the business, advocating for analytics and establishing expertise in the field. Essential skills include driving commercial value across sectors, deploying analytical outputs, utilizing visualization tools, and leading global teams. Strong communication skills, ability to set direction and deliver on vision, technical knowledge of big data platforms, and project management experience are required. Desirable skills involve experience in the Financial Services industry, knowledge of internal systems and data warehouse environments, and expertise in analytical areas like Targeting, Segmentation, Pricing, and more. Purpose of the role: To extract insights from complex data sets, develop decision models, and present recommendations to stakeholders. Accountabilities: - Identify and extract relevant data - Perform sensitivity analysis and scenario planning - Monitor existing model performance - Implement data quality control procedures - Build and validate quantitative models Director Expectations: - Manage a business function and contribute to strategic initiatives - Lead a team, embed a performance culture, and provide expert advice - Manage resourcing, budgeting, and policy creation - Foster compliance and observe regulations - Demonstrate industry knowledge and analytical skills - Negotiate with stakeholders and act as a spokesperson for the function Leadership Behaviors: - Listen and be authentic - Energize and inspire - Align across the enterprise - Develop others Barclays Values: - Respect - Integrity - Service - Excellence - Stewardship Barclays Mindset: - Empower - Challenge - Drive,

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams

Perform advanced analytics and statistical modeling Build predictive and ML models Collaborate with remote teams