101 Azure Ml Jobs

Job Responsibilities: Lead end-to-end development of ML/DL models from data preprocessing to model deployment Design and implement advanced solutions using computer vision, NLP, and generative AI models (e g , Transformers, GANs) Apply and experiment with agentic AI approaches to build autonomous decision-making systems Collaborate with engineering, product, and business stakeholders to align AI solutions with business outcomes Work with large-scale datasets and implement MLOps pipelines for automated training, evaluation, and deployment on cloud (Azure preferred) Stay up to date with the latest AI research and apply state-of-the-art techniques in production systems Mentor junior data scientists and contribute to AI knowledge sharing across teams Desired Skill: 8+ years of industry experience in data science, ML, or AI, with demonstrated project ownership Proficiency in Python and frameworks like TensorFlow, PyTorch, OpenCV, scikit-learn, etc Strong background in generative models (eg , LLMs, GANs, VAEs) and foundational ML techniques Expertise in computer vision, including object detection, image classification, and segmentation Experience in implementing agentic AI systems using modern orchestration tools and frameworks Hands-on experience with Azure AI services (e g, Azure ML, Cognitive Services, Azure OpenAI, Azure Blob for data handling) Solid understanding of MLOps practices (CI/CD, version control, model registry, monitoring) Strong analytical, problem-solving, and communication skills Value Add (If Any): Should have worked as a Team Leader Purely Data Science profile with ML, GenAi, Python exp Good exp in GenAI, ML Notice period- Immediate Qualification : Any Tech degree, masters Candidates should report in office for a period of 6 months, later it will can be a Hybrid work mode 1 round of interview F2F must, 2 Technical, 1 Project Delivery exp is a must Should know about project deliverables Should have at least 3 project deliveries, real time Notice Period : Immediate to 15 days

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As a Power BI developer, you will require the following skills: - Advanced skills and experience with Power BI Report Development (Pro License) and Proficient in Power BI Service Management. - Strong understanding of Data Analysis Expressions (DAX). - Advanced knowledge of ETL processes with Power Query. - Experience in building complex Power BI dashboards and expert in visualization. - Design and create SQL queries, interpret advanced SQL queries, and extract or manipulate data for reporting and analysis purposes. - Advanced proficiency in MS Excel and Excel 365 complex functions. - Knowledge in Power Platform tools such as Power Apps, Power Automate, and Power Pages. Good to have Skills: - Experience in managing a similar reporting and analysis function. - Experience with Alteryx and Azure ML / Python. - Command on Mathematical concepts especially statistics and probability. - Drive, design, develop, deploy, and maintain a BI-driven transformation of business and financial reporting using Power BI and SQL. Your role and responsibilities will include: - Designing, developing, deploying, and maintaining BI interfaces, including data visualizations, dashboards, and reports using Power BI. - Developing and executing database queries and conducting analyses to optimize the performance of Power BI reports. - Collaborating with cross-functional teams to gather reporting requirements and translate them into actionable insights. - Analyzing complex data sets and providing business insights and recommendations to support decision-making processes. - Ensuring data accuracy and integrity by conducting regular reviews, data validation, troubleshooting, and documentation. - Participating in the design and implementation of data governance policies and procedures. - Enhancing efficiency through Lean methodologies, automation, and digital integration to improve processes and foster business growth. - Staying up-to-date with industry trends and advancements in reporting and analytics tools and techniques. Requirements: - Passionate about data analysis, reporting, and have a strong command of power platform tools, along with SQL Server Management Studio skills to handle the backend data. - Proven experience as a Reporting and Analytics Specialist, Business Intelligence Analyst, or similar role. - Excellent analytical and problem-solving skills with the ability to turn complex data into actionable insights. - Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders. - Attention to detail and strong organizational skills to handle multiple tasks and meet deadlines. - Continuous learning mindset and the ability to adapt to evolving reporting and analytics technologies. At EY, we exist to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

You are an exceptional AI Architect with expertise in Agentic AI and Generative AI, responsible for leading the design, development, and deployment of next-generation autonomous AI systems. Your role involves building LLM-powered agents with memory, tool use, planning, and reasoning capabilities to create intelligent, goal-driven systems. As a technical leader, you will oversee end-to-end AI initiatives, from research and architecture design to deployment in cloud environments. Your key responsibilities include designing and implementing LLM-based agents for autonomous task execution, memory management, tool usage, and multi-step reasoning. You will develop modular, goal-oriented agentic systems using tools like LangChain, Auto-GPT, CrewAI, SuperAGI, and OpenAI Function Calling. Additionally, you will design multi-agent ecosystems with collaboration, negotiation, and task delegation capabilities while integrating long-term and short-term memory into agents. You will also be responsible for developing, fine-tuning, and optimizing foundation models like LLMs and diffusion models using TensorFlow, PyTorch, or JAX. Applying model compression, quantization, pruning, and distillation techniques for deployment efficiency will be part of your role. Leveraging cloud AI services such as AWS SageMaker, Azure ML, and Google Vertex AI for scalable model training and serving is also crucial. Your tasks will include leading research in Agentic AI, LLM orchestration, and advanced planning strategies. Staying updated with state-of-the-art research and contributing to whitepapers, blogs, or conferences like NeurIPS, ICML, and ICLR will be expected. Evaluating new architectures such as BDI models, cognitive architectures, or neuro-symbolic approaches will be part of your responsibilities. Strong coding proficiency in Python, CUDA, and TensorRT for model acceleration is required, along with experience in distributed computing frameworks like Ray, Dask, and Apache Spark for training large-scale models. Designing and implementing robust MLOps pipelines using Docker, Kubernetes, MLflow, and CI/CD systems is essential. To excel in this role, you should have at least 8-14 years of experience in AI/ML, with a minimum of 2+ years of hands-on experience with Agentic AI systems. Proven experience in building, scaling, and deploying agent-based architectures is necessary. A strong theoretical foundation in machine learning, deep learning, NLP, and reinforcement learning is crucial, along with familiarity in cognitive architectures, decision-making, and planning systems. Hands-on experience with LLM integration and fine-tuning, including OpenAI GPT-4, Claude, LLaMA, Mistral, and Gemini, is required. Preferred qualifications include publications or open-source contributions in Agentic AI or Generative AI, experience with simulation environments like OpenAI Gym or Unity ML-Agents for training/test agents, and knowledge of safety, ethics, and alignment in autonomous AI systems.,

Please look for a mid-senior level profile with 68 years of experience. The primary skill set is Data Scientist with strong Azure experience , The candidate should have expertise in the following areas: Core Expertise • End-to-end data science workflow: data preparation, feature engineering, model building, validation, and deployment • Proficiency in descriptive and inferential statistics • Algorithm development for solving business problems Azure Cloud Skills • Hands-on experience with Azure Machine Learning, Databricks, Synapse Analytics, and Data Explorer (KQL) • Skilled in using Azure Notebooks and integrating Azure services with open-source frameworks Programming & Tools • Strong command of Python and R • Practical experience with libraries like scikit-learn, pandas, NumPy, TensorFlow, and PyTorch • SQL proficiency for data manipulation and database management Integration & Deployment • Ability to integrate Azure tools with popular ML frameworks • Experience in cloud-based model deployment, monitoring, and scaling Analytical & Conceptual Strengths • Advanced analytical thinking and problem-solving • Experience in exploratory data analysis (EDA) • Awareness of security and compliance in data science workflows • Hope this helps.

Bright Vision Technologies is offering an immediate Full-time opportunity for an AI/ML Engineer. At Bright Vision Technologies, we are dedicated to transforming aspirations into reality, providing growth opportunities for IT professionals and recent graduates alike. We have a successful track record of over a decade in H1B filings and offer end-to-end support, transparent processes, access to top clients, and green card sponsorship for eligible candidates. As an AI/ML Engineer at Bright Vision Technologies, you will be responsible for building scalable machine learning models, deploying them using AWS SageMaker or Azure ML, collaborating with data engineers for seamless integration, designing and implementing models using scikit-learn or TensorFlow, developing and maintaining APIs using RESTful principles, and troubleshooting and resolving complex technical issues related to AI/ML and data engineering. To qualify for this opportunity, you should have a minimum of 7+ years of experience in AI/ML development, excellent programming skills, a passion for delivering high-quality solutions, and good communication skills to work collaboratively with clients and team members. Please note that as part of the H-1B visa sponsorship process, there are various fees and expenses associated with filing and processing the application. While we are committed to supporting you through this process, we kindly request that candidates cover some of the costs such as premium processing (if applicable) and dependent visa fees. However, we will reimburse 50% of the fee after 4 years of continuous employment with us. If you are interested in exploring this opportunity further, kindly send your resume directly to Darshan at darshan@bvteck.com. For immediate consideration, you can contact us at the provided phone numbers. Thank you for considering our offer, and we look forward to hearing from you soon.,

Education Bachelors or Masters degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative discipline; PhDs preferred Specialization or research in applied machine learning, MLOps, or ML systems preferred Experience 7+ years of experience designing, developing, and deploying ML models in production environments 4+ years of experience in building predictive models like classification, time series modelling etc. 1+ year of experience in areas such as recommendation systems, pattern recognition, NLP Experience with production-grade Python (preferred), as well as Java or C/C++ Hands-on experience with large-scale software architecture, APIs, and model versioning systems Skills Expertise in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn Proficient in cloud-based ML platforms (e.g., Azure ML, Google Cloud Platform, AWS SageMaker) Solid understanding of machine learning algorithms (e.g., classification, regression, SVMs, ARIMA, ensemble methods, deep learning, neural network) Strong foundation in probability theory and statistical modeling (generative and discriminative) Familiarity with DevOps/MLOps practices, CI/CD pipelines, GitHub Actions, Terraform Docker, and Kubernetes Ability to communicate technical concepts clearly to both technical and non-technical takeholders Strong collaboration skills with cross-functional teams (engineering, analytics, product) Ability to independently manage tasks and thrive in a remote-first or hybrid environment Preferred Skills Experience in regulated industries (e.g., finance, healthcare, insurance) Excellent communication and stakeholder engagement skills Strong understanding of deep learning architectures (e.g. CNNs, RNNs, Transformers, GANs) Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.) Proficiency in model evaluation, distributed training, and hyperparameter optimization Proficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search) Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes) Proficient in API and Microservices technologies Track records in large-scale, real-time AI/GenAI/ML database and solution technologies Background in responsible AI/ML, model interpretability, and fairness auditing Experience : 7 +Years Location :Remote, Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune

You will be working with Hitachi Solutions India Pvt Ltd, a core member of Information & Telecommunication Systems Company of Hitachi Group, recognized for delivering business and IT strategies and solutions across various industries. Hitachi Solutions offers value-driven services throughout the IT life cycle, from systems planning to integration, operation, and maintenance. The company delivers superior products and services globally through its subsidiaries in the US, Europe, China, and India, focusing on solutions for social innovation such as smart cities. In a dynamic and rewarding work environment, you will collaborate with an experienced leadership team, possess strong technology expertise, and maintain robust relationships with a wide customer and partner base. Hitachi Solutions provides a competitive compensation and benefits package, regular performance reviews, bonuses, and ongoing training opportunities. At Hitachi Solutions, we pride ourselves on being industry leaders and fostering a work environment where personal and professional growth is encouraged. Our commitments to employees include recognizing that profitability and success stem from our team's efforts, offering challenging work across diverse industries, and acknowledging the importance of continual learning and personal growth. We value individual contributions and are committed to creating an enriching environment through open communication. **Job Description** **Title**: Azure Development **Experience Level**: 3 ~ 8 years **Position**: Consultant/ Senior Con/ Specialist **Primary Skills**: - Working experience in Microsoft Azure Stack IoT Hub, Event Hub, Azure Functions, Azure Logic Apps, Azure Data Factory, Cosmos DB, Azure Databricks, Azure ML, IoT Edge, Docker, Python - Good knowledge of using Serverless Functions (Using Java/Python), App services, Azure Kubernetes services, etc. - Experience in configuring & monitoring attributes, handling scale-up/down scenarios for Network Service Components on Azure - Any experience in implementing Azure security, authentication, and single sign-on **Secondary Skills**: - Deploying cloud applications in Azure following industry best practices - Detailed design of cloud applications including design patterns and principles - Experience in performance tuning of cloud-based applications - Working in an agile/DevOps environment with CI/CD pipelines, Git Hub/Bitbucket - Automation tools like Jenkins, Puppet, Ansible, Terraform - Microsoft certification on Azure Development preferred **Additional Skills Required**: - Working with Azure Kubernetes, DevOps, Microservices, Azure Service, Media services, Azure Service Bus, Azure storage, Azure AI modules - Leveraging Cloud-Based Machine Learning on Azure **Key Responsibilities**: - Implementing highly scalable solutions - Translating business requirements into viable technical design and implementation - Understanding and improving current applications and technical architecture - Following software development lifecycle and structured implementation approach - Code review, ensuring project quality, and resolving performance issues,

Intellectt Inc. is seeking AI Product Engineers to join our team and contribute to our expanding AI-focused product portfolio. As an AI Product Engineer, you will play a crucial role in bridging the gap between product development and advanced AI technologies. This position requires a deep understanding of AI models, APIs, and data pipelines, along with a strong focus on product design, user experience, and deployment strategies. Key Responsibilities - Collaborate with product managers and AI teams to design and develop AI-driven products leveraging LLMs such as GPT-3.5, GPT-4, and Gemini. - Translate business requirements into AI product features and develop functional prototypes. - Implement LangChain-based workflows, including LangSmith and LangGraph, to enable intelligent app interactions. - Integrate Retrieval-Augmented Generation (RAG) pipelines and vector databases like ChromaDB to enhance AI performance. - Customize model outputs based on product needs and use cases through prompt engineering. - Develop REST APIs and microservices using Flask or FastAPI to facilitate model integration. - Manage and process structured and unstructured data using SQL, PySpark, and Spark SQL. - Collaborate with UI/UX teams to ensure seamless user interaction with AI components. - Support product deployment and monitoring on Azure ML or AWS Bedrock. Required Skills - Proficiency in Python, SQL, PySpark, and Spark SQL for programming and data processing. - Understanding of Generative AI, LLMs, and prompt engineering. - Experience with LangChain, LangGraph, and LangSmith for workflow development. - Familiarity with vector databases and embedding techniques for AI applications. - Exposure to cloud platforms such as Azure ML or AWS Bedrock. - Development of REST APIs using Flask or FastAPI. - Strong problem-solving skills and a product-oriented mindset. Preferred Qualifications - Bachelor's degree in Computer Science, AI/ML, Data Science, or related field. - Internship or academic experience in AI product development or applied NLP. - Knowledge of MLOps concepts and product lifecycle best practices. - Basic understanding of UI/UX principles and user-centric design. Join our team at Intellectt Inc. and be part of our mission to drive innovation through Artificial Intelligence and Digital Transformation services. Your expertise as an AI Product Engineer will contribute to building impactful, intelligent solutions that shape the future of technology.,

The ML Platform Specialist role involves designing, implementing, and maintaining machine learning infrastructure and workflows on the Databricks Lakehouse Platform. Your primary responsibility will be to ensure the successful deployment, monitoring, and scaling of machine learning models across the organization. You will design and implement scalable ML infrastructure on the Databricks Lakehouse Platform, develop CI/CD pipelines for machine learning models, and create automated testing and validation processes using Databricks MLflow. Additionally, you will be responsible for managing model monitoring systems, collaborating with various teams to optimize machine learning workflows, and maintaining reproducible machine learning environments using Databricks Notebooks and clusters. Furthermore, you will implement advanced feature engineering and management using the Databricks Feature Store, optimize machine learning model performance, and ensure data governance, security, and compliance within the Databricks environment. Your role will also involve creating and maintaining comprehensive documentation for ML infrastructure and processes, as well as working across teams from multiple suppliers to drive continuous improvement and transformation initiatives for MLOps/DataOps. To be successful in this role, you should have a Bachelor's or Master's degree in computer science, Machine Learning, Data Engineering, or a related field, along with 3-5 years of experience in ML Ops with expertise in Databricks and/or Azure ML. You should possess advanced proficiency with the Databricks Lakehouse Platform, strong experience with Databricks MLflow, and expert-level programming skills in Python, including knowledge of PySpark, MLlib, Delta Lake, and Azure ML SDK. Moreover, you should have a deep understanding of Databricks Feature Store and Feature Engineering techniques, experience with Databricks workflows and job scheduling, and proficiency in machine learning frameworks compatible with Databricks and Azure ML such as TensorFlow, PyTorch, and scikit-learn. Knowledge of cloud platforms like Azure Databricks, Azure DevOps, and Azure ML, as well as exposure to Terraform, ARM/BICEP, distributed computing, and big data processing techniques, will be essential for this role. Experience with Containerization, WebApps Kubernetes, Cognitive Services, and other MLOps tools will be considered a plus, as you contribute to the continuous improvement and transformation of MLOps/DataOps in the organization.,

As a Lead Data Scientist at our organization, you will be part of our high-performing team which was honored with the prestigious "Outstanding Data Engineering Team" Award at DES 2025 for setting new benchmarks in data excellence. In this role, we are looking for a highly skilled and GCP-certified AI/ML Engineer with expertise in Generative AI models, Natural Language Processing (NLP), and cloud-native development. With at least 8 years of experience, you will be responsible for designing and deploying scalable ML solutions, building robust APIs, and integrating AI capabilities into enterprise applications. The ideal candidate should also have a solid background in software engineering and DevOps practices. Your key responsibilities will include designing, developing, and implementing GenAI and NLP models using Python and relevant libraries, deploying ML models and pipelines on GCP and Azure ML/Azure Services, developing and managing RESTful APIs for model integration, applying ML Ops and CI/CD best practices, ensuring solutions follow software engineering principles, working in Agile teams, collaborating with cross-functional teams, optimizing performance and cost efficiency of deployed models and cloud services, and maintaining strong documentation while following secure coding and data privacy standards. The required skills for this role include strong programming skills in Python with experience in ML & NLP frameworks, experience with Generative AI models, solid understanding of NLP concepts, proficiency in GCP services, familiarity with Azure services, experience in building and managing REST APIs, hands-on experience with CI/CD tools and containerization, and a strong grasp of software engineering concepts and Agile methodology. Preferred qualifications for this position include a Bachelor's or Master's degree in Computer Science, Data Science, or related field, experience working with cross-platform AI integration, exposure to LLM Ops / Prompt Engineering, and certifications in Azure AI Engineer or Azure Data Scientist. This position is based in Chennai, Coimbatore, Pune, or Bangalore, and requires a minimum of 8-12 years of experience. Join us and be part of a dynamic team driving innovation in the field of data science.,

You are looking for a Senior ML Engineer (MLOps) with 3-5 years of experience to join the team in either Kochi or Chennai. In this role, you will be responsible for taming data by pulling, cleaning, and shaping structured & unstructured data. You will orchestrate pipelines using tools like Airflow, Step Functions, or ADF. Additionally, you will be involved in shipping models by building, tuning, and deploying them to production on platforms like SageMaker, Azure ML, or Vertex AI. Scaling using Spark or Databricks for heavy lifting and automating processes using Docker, Kubernetes, CI/CD, MLFlow, Seldon, and Kubeflow will also be a part of your responsibilities. Collaboration with engineers, architects, and business professionals to solve real problems efficiently is key in this role. To be successful in this position, you should have at least 3 years of hands-on MLOps experience with a total of 4-5 years in software development. Proficiency in one hyperscaler platform (AWS, Azure, or GCP), familiarity with Databricks, Spark, Python, SQL, and machine learning libraries like TensorFlow, PyTorch, or Scikit-learn is essential. Debugging Kubernetes, working with Dockerfiles, and prototyping with open-source tools are skills that are highly valued. A sharp mind, willingness to take action, and a collaborative attitude are qualities that will contribute to your success. Experience with Sagemaker, Azure ML, or Vertex AI in a production environment is a plus. A passion for writing clean code, maintaining clear documentation, and submitting concise pull requests is also appreciated. Joining Datadivr offers you the opportunity to work in a domain-specific environment focused on F&B, where your work directly impacts operations. As part of a small team, you will have significant autonomy and ownership over the projects you work on. To apply for this position, please submit your CV along with a brief description of a project you have shipped to careers@datadivr.com or via direct message. The company ensures a response to all serious applicants and welcomes referrals from those who know suitable candidates.,

SettleMint is an innovative Blockchain development platform that enables your engineering team to create, integrate, and launch various Blockchain applications efficiently. With headquarters in Belgium and a global presence, including offices in India, Singapore, Dubai, Tokyo, and the UK, SettleMint has recently secured Series-A funding of 16 Million. SettleMint India, established in 2019 with its headquarters in Delhi, focuses on delivering client projects and developing high-performance low-code Blockchain solutions. As a Senior Machine Learning Engineer at SettleMint India, you will utilize your extensive experience in AI and machine learning to lead impactful initiatives within the company. Working closely with cross-functional teams, you will identify business challenges, design data-driven solutions, and provide actionable insights to drive innovation. Key Responsibilities: - Lead and oversee the machine learning team, including recruitment, performance management, and professional growth. - Develop and implement the company's machine learning strategy. - Collaborate in agile/scrum processes to design, test, deploy, and support machine learning models integrated with various applications. - Mentor junior ML engineers on technical competencies. - Generate insights from data sets, identify trends, and prepare reports using data visualization. Requirements: - Proven experience in implementing and deploying ML solutions at scale for real-world problems. - Strong expertise in Machine Learning, Deep Learning, Image Processing, NLP, predictive & forecasting models. - Familiarity with AWS Sagemaker/Azure ML and advanced SQL. Experience with Pyspark and cloud platforms like AWS. - Hands-on experience with big data technologies such as Hadoop, Spark, and NoSQL. - Proficiency in Python Data Analysis Stack (Pandas, Numpy, Scikit-learn). - Curiosity to learn and implement the latest developments in AI. - Self-motivated, independent worker with a keen eye for detail. What SettleMint Offers: - A dynamic work environment that evolves as the company grows. - Trust in your abilities to deliver project outcomes without micro-management. - Focus on employee well-being and continuous learning and development opportunities. - Exposure to global projects and collaboration with international teams. Join SettleMint India to be a part of a pioneering team driving innovation in Blockchain technology and machine learning applications.,

As a Software Engineer II - AI/ML Engineer at Electronic Arts, you will be part of the EA Digital Platform (EADP) group, the core that powers the global EA ecosystem. You will contribute to creating next-level entertainment experiences by working on a large-scale distributed data system that enables EA Games to personalize player experience and engagement. Your role will involve designing, implementing, and optimizing the infrastructure for the AI model training and deployment platform, integrating AI capabilities into existing software systems, and developing tools to monitor the platform's performance in real-time. You will collaborate with a team of developers to ensure code quality through code reviews, maintain best practices, and enhance platform features under senior guidance. Additionally, you will work on improving the stability and observability of the platform to ensure seamless operations. Your expertise in software development, model development, and experience with programming languages such as Go, Java, or Scala, along with scripting languages like bash, awk, and python, will be crucial in this role. You should also have hands-on experience with Deep Learning frameworks like PyTorch, TensorFlow, CUDA, and ML Platforms such as Sagemaker, Azure ML, or GCP Vertex AI. To qualify for this position, you should possess a Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a related field, along with at least 3 years of relevant experience. Your experience with cloud services, modern data technologies, data streaming, and processing systems will be beneficial for this role. Electronic Arts values adaptability, resilience, creativity, and curiosity, and offers a holistic approach to benefits programs to support your physical, emotional, financial, career, and community wellness. Join us in shaping the future of play and be part of a community where everyone contributes to making play happen.,

As the AI Platform Lead at a leading Technology company based out of Noida Sector -16, with a global presence and a workforce of 17,000+ employees across 34 countries, you will play a crucial role in driving the evolution and operational excellence of the AI Platform within the organization. In this permanent position with a hybrid work mode, you will be responsible for overseeing key systems such as Dataiku, Azure ML, and Azure AI Services to deliver scalable, robust, and innovative solutions supporting enterprise initiatives. Your main responsibilities will include supervising platform operations, maintaining Dataiku and Azure components for high availability, performance, and scalability. You will also oversee the maintenance and optimization of Azure cloud infrastructure to ensure security, reliability, and scalability. Additionally, you will establish best practices, governance policies, and security standards across all AI operations, monitor platform usage and performance metrics, and drive continuous improvement. You will be expected to evaluate emerging AI services and technologies, lead and collaborate with a diverse team, manage budget and cost allocation for the AI Platform efficiently, and provide regular updates to the Head of Data and Platforms on the platform status, risks, and resource needs. To be successful in this role, you should have a proven track record with more than 5 years of experience in AI/ML platform management, a strong knowledge of machine learning, data analytics, and cloud computing, and hands-on experience with technologies such as Dataiku, Azure ML, and Azure AI Foundry. You should be well-versed in agile methodologies, DevOps practices, and CI/CD pipeline management, with the ability to manage multiple priorities in a fast-paced environment. Experience in leading cross-functional teams and executing large-scale technology initiatives is essential, and skills and experience in Agile methodologies are a plus. The ideal candidate will have a proactive mindset focused on leveraging AI to drive business value, experience with budget oversight and resource allocation, and knowledge of the software development lifecycle and agile methodologies. A minimum of 5 years of work experience in AI/ML Platform management or related fields and an advanced degree (Masters or PhD preferred) in Computer Science, Data Science, Engineering, or a related field are required for this position.,

Qualcomm India Private Limited is a leading technology innovator in the Engineering Group, specifically in Systems Engineering. As a Qualcomm Systems Engineer, you will be involved in researching, designing, developing, simulating, and validating systems-level software, hardware, architecture, algorithms, and solutions to drive the development of cutting-edge technology. Collaboration across functional teams is essential to meet and exceed system-level requirements and standards. To qualify for this role, you should possess a Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with at least 8 years of experience in Systems Engineering. Alternatively, a Master's degree with 7+ years of experience or a Ph.D. with 6+ years of experience in the same field is also acceptable. Currently, Qualcomm is seeking a Principal AI/ML Engineer with expertise in model inference, optimization, debugging, and hardware acceleration. The role focuses on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across various hardware platforms. In addition to hands-on engineering tasks, the role also involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques. The ideal candidate will collaborate with researchers, industry experts, and open-source communities to enhance AI performance continuously. The suitable candidate should have a minimum of 20 years of experience in AI/ML development, with a focus on model inference, optimization, debugging, and Python-based AI deployment. A Master's or Ph.D. in Computer Science, Machine Learning, or AI is preferred. Key Responsibilities of this role include Model Optimization & Quantization, AI Hardware Acceleration & Deployment, and AI Research & Innovation. The candidate should have expertise in optimizing deep learning models, familiarity with deep learning frameworks, proficiency in CUDA programming, and experience with various ML inference runtimes. Qualcomm encourages applicants from diverse backgrounds and is an equal opportunity employer. The company is committed to providing reasonable accommodations to individuals with disabilities during the hiring process. It is vital for all employees to adhere to applicable policies and procedures, including those related to confidentiality and security. Qualcomm does not accept unsolicited resumes or applications from staffing and recruiting agencies. For further information about this role, interested individuals may reach out to Qualcomm Careers.,

As a member of KPMG in India, you will be part of a professional services firm affiliated with KPMG International Limited. Established in India in August 1993, KPMG professionals leverage a global network of firms while being well-versed in local laws, regulations, markets, and competition. With offices across various Indian cities, including Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara, and Vijayawada, we offer services to national and international clients across diverse sectors. Your role involves collaborating with business stakeholders and cross-functional subject matter experts to gain a deep understanding of the business context and key questions. You will be responsible for creating Proof of Concepts (POCs) and Minimum Viable Products (MVPs), guiding them through production deployment and operationalization. Additionally, you will play a crucial role in influencing machine learning strategy for Digital programs and projects, ensuring that solution recommendations strike a balance between speed to market and analytical soundness. Utilizing a variety of commercial and open-source tools such as Python, R, and TensorFlow, you will develop analytical and modeling solutions. By combining machine learning algorithms with other techniques, you will formulate model-based solutions and design algorithms to extract information from large datasets. Your responsibilities will also include deploying algorithms to production, comparing results from different methodologies, and recommending optimal techniques. Furthermore, you will work on multiple pillars of Artificial Intelligence (AI), including cognitive engineering, conversational bots, and data science. It will be essential to ensure that solutions demonstrate high levels of performance, security, scalability, maintainability, and reliability upon deployment. Your role will involve leading discussions, providing thought leadership, and sharing subject matter expertise in machine learning techniques, tools, and concepts. To be successful in this role, you are required to have a Bachelor of Science or Bachelor of Engineering at a minimum. A combination of business focus, strong analytical and problem-solving skills, and programming knowledge is necessary to iterate quickly through the discovery phase of projects. Proficiency in statistical concepts, machine learning algorithms, and programming languages like R and Python is crucial. Additionally, experience with data management tools such as Microsoft Azure or AWS is preferred. You should possess good knowledge of Agile principles and processes, the ability to lead and manage teams effectively, and excellent communication skills. Being a self-motivated problem solver who can work independently and collaboratively is essential for this position. If you are passionate about data science, machine learning, and driving impactful business results through innovative solutions, we encourage you to apply. Qualifications: - Bachelor of Science or Bachelor of Engineering at a minimum - Strong analytical and problem-solving skills - Proficient in statistical/programming software and data querying languages - Experience with Microsoft Azure or AWS data management tools - Knowledge of descriptive and exploratory statistics, predictive modeling, and machine learning algorithms - Proficiency in Agile principles and the ability to lead and manage teams - Excellent communication and presentation skills If you hold a B.Tech, M.Tech, MCA, or M.Sc degree and meet the above qualifications, we invite you to join our team and contribute to our mission of delivering cutting-edge solutions to our clients.,

As an AI & Machine Learning Engineer specializing in Azure OpenAI, Agent AI, and Data Science solutions, you will be responsible for developing AI-driven solutions and deploying ML models. Your expertise in Python, TensorFlow, and ML model development will be crucial for predictive analytics and automation. You should have a strong background in Azure cloud services, particularly Azure Machine Learning, Azure OpenAI, and Data Engineering. Additionally, some experience with Microsoft technologies such as .NET, C#, and Azure-based enterprise applications would be beneficial for this role. Your primary responsibilities will include developing AI models using Azure OpenAI and Agent AI, as well as working on Machine Learning and Data Science projects using Python and TensorFlow. Knowledge of cloud computing, specifically Azure ML and Azure Cognitive Services, will be essential to integrate AI with cloud applications. Your passion for building AI-driven solutions and deploying ML models, combined with your skills in AI model deployment and some knowledge of API integration, will be key to your success in this role. If you are enthusiastic about working with cutting-edge technologies and driving innovation in the field of AI and Machine Learning, this position is perfect for you.,

Role We are seeking a seasoned AI/ML Engineer to join our Cloud Operations (CloudOps) team. The ideal candidate should have strong expertise in designing, developing, and deploying AI/ML models and automation solutions that optimize cloud infrastructure management and operational efficiency. Primary Responsibilities - Design, develop, and deploy machine learning models and AI algorithms to automate cloud infrastructure, monitoring, fault detection, and predictive maintenance. - Collaborate with Cloud Engineers, ML Engineers, Data Scientists, and DevOps teams to to integrate AI/ML solutions into cloud orchestration and management platforms. - Build scalable data pipelines and workflows using cloud-native services (preferably AWS, GCP) for real-time and batch ML model training and inference. - Analyze large volumes of cloud telemetry data (logs, metrics, traces) to extract actionable insights using statistical methods and ML techniques. - Implement anomaly detection, capacity forecasting, resource optimization, and automated remediation solutions. - Develop APIs and microservices to expose AI/ML capabilities for CloudOps automation. - Work with SecOps to ensure ML models comply with privacy, and governance standards. - Optimize existing AI/ML workflows for cost, performance, and accuracy. - Stay updated with the latest trends in AI/ML, cloud computing, and infrastructure automation. Skills & Requirements - 6+ years of professional experience in AI/ML engineering, preferably in cloud infrastructure or operations environments. - Strong proficiency in Python (relevant libraries such as pandas and numpy) or R, or similar programming languages used in AI/ML development. - Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or similar. - Hands-on experience with MCP Server, AI Agents, and A2A (Agent-to-Agent) communication - Experience with Large Language Model (LLM) operations (LLM Ops) - Expertise in cloud platforms (AWS, Azure, or GCP) and their AI/ML services (e.g., SageMaker, Bedrock, Anthropic, Azure ML, OpenAI, Vertex AI). - Strong understanding of data structures, algorithms, and statistical modeling. - Experience building and maintaining data pipelines using tools like Apache Spark, Kafka, Airflow, or cloud-native alternatives. - Knowledge of containerization and orchestration (Docker, Kubernetes) to deploy ML models in production. - Familiarity with infrastructure monitoring tools (Prometheus, Grafana, ELK Stack) and cloud management platforms. - Experience with CI/CD pipelines and automation tools in cloud environments. - Excellent problem-solving skills and ability to work independently as well as in cross-functional teams. - Strong communication skills for collaborating with technical and non-technical stakeholders. - Knowledge of Infrastructure as Code (IaC) tools like Terraform, CloudFormation. - Experience with cybersecurity principles related to cloud and AI/ML systems.

We are seeking a highly skilled Staff Machine Learning Engineer with a strong background in Machine Learning and Software Engineering to join our team. In this role, you will collaborate closely with product managers, applied scientists, and engineers to design, implement, and scale ML-powered systems that extract and reason over information from complex, unstructured data sourcessuch as documents, web screens, and automation workflows. Your work will play a key role in enabling intelligent, context-aware assistants and task automation agents that understand user intent and deliver meaningful outcomes. Key Responsibilities Build intelligent agentic systems that combine document understanding, retrieval, and LLM-based reasoning to support context-aware conversational workflows. Design and implement scalable Agentic RAG pipelines that orchestrate unstructured data preprocessing, vector store integration, and LLM prompting for accurate, grounded responses. Develop modular ML components for layout analysis, information extraction, dialogue management, and tool invocation within multi-turn, goal-driven conversations. Integrate conversational agents with enterprise data sources, APIs, and downstream automation workflows to enable end-to-end task execution. Craft dynamic prompting and memory strategies to maintain context, reduce hallucination, and improve relevance in long-form or multi-turn queries. Collaborate cross-functionally with product managers, UX designers, and platform engineers to define agent behavior and ensure seamless user experiences. Monitor and continuously improve system performance, including response quality, retrieval precision, latency, and task success rate using real-world feedback. Drive data curation efforts including synthetic generation, annotation workflows, and hard example mining to improve agent robustness and generalization. Establish best practices for evaluating agent behavior, including human-in-the-loop review processes, regression testing, and safety guardrails. Contribute to infrastructure and MLOps pipelines that support model experimentation, deployment, and monitoring in production environments. Qualifications / Expectations: Bachelors or Masters Degree in Computer Science, Data Science, or a related technical field. Advanced degrees are a plus. 5–7+ years of hands-on experience in building and deploying machine learning models, with a strong focus on document intelligence, NLP, or Generative AI. Proven experience developing and productionizing ML systems for unstructured data processing, including document parsing, table extraction, and layout analysis. Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and experience with OCR and document processing tools (e.g., Tesseract, AWS Textract, PDFMiner, LayoutParser). Strong experience with LLMs and Retrieval-Augmented Generation (RAG) architectures, including practical knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks. Understanding on knowledge graphs and graph based information retrieval Experience designing and integrating conversational agents with context memory, function/tool calling, and dynamic prompting strategies. Familiarity with vector stores (e.g., FAISS, Pinecone, Weaviate) and search/retrieval mechanisms for grounding LLM outputs. Experience building ML pipelines and implementing MLOps best practices to support training, validation, deployment, and monitoring of models at scale. Hands-on experience with cloud ML services (e.g., AWS SageMaker, Azure ML, Google Vertex AI) for training and inference. Solid programming skills in Python, with working knowledge of SQL Experience with containerization (Docker), orchestration (Kubernetes), and model serving technologies (e.g., Triton Inference Server, ONNX Runtime, TorchServe) in production environments. Knowledge of model optimization techniques (e.g., quantization, pruning, distillation) to improve inference efficiency on cloud or edge devices. Strong problem-solving abilities, with a track record of delivering scalable, high-impact ML solutions for complex, real-world problems. Excellent communication skills and ability to work autonomously in a fast-paced, collaborative environment. Nice to Have: Experience in fine-tuning large language models (LLMs) and applying GenAI techniques in parsing unstructured data. Experience with dialogue management systems or conversational frameworks (e.g., Rasa, Dialogflow, or custom pipelines) for building intelligent agents. Experience with distributed training techniques to optimize large-scale model training across multiple GPUs or cloud environments. Understanding of prompt engineering best practices and few-shot or chain-of-thought prompting for improving agent behavior in GenAI systems. Background in open-source contributions or research related to document AI, LLM applications, or multi-modal learning. Familiarity with CI/CD pipelines for ML, automated model versioning, and monitoring tools for performance and drift in production models.

As a Machine Learning Engineer, your primary responsibility will be to develop, train, and validate predictive and analytical models using machine learning techniques. You will collaborate closely with data engineers and business teams to define data requirements and success metrics. In addition, you will deploy machine learning models into production following ML Ops best practices and build automated pipelines for model training, testing, monitoring, and retraining. Your role will also involve optimizing model performance, ensuring scalability and reliability, monitoring model drift and performance degradation, and continuously improving the models. Furthermore, you will implement CI/CD practices for machine learning workflows. To excel in this role, you must possess a strong proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, and PyTorch/TensorFlow. Experience with ML Ops tools/frameworks like MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML is essential. A good understanding of data engineering concepts such as ETL, data pipelines, and APIs is required, along with hands-on experience in containerization and orchestration using Docker and Kubernetes. Knowledge of cloud platforms like AWS, GCP, or Azure for ML model deployment is also crucial. Your background should include a strong foundation in statistics, machine learning algorithms, and model evaluation techniques, along with familiarity with version control using Git and CI/CD pipelines. Ideally, you should hold a Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. Previous experience in handling large-scale data pipelines and real-time model serving will be advantageous. Exposure to feature stores and automated model monitoring is a plus. Strong problem-solving, analytical, and communication skills are highly desirable for this role.,

Tezo is a new generation Digital & AI solutions provider focused on delivering exceptional experiences using cutting-edge analytics, technology, and digital excellence. We are currently looking for a highly experienced and dynamic Practice Head specializing in Data Science & AI to lead our data practice in Hyderabad. This role is perfect for a technology leader with a solid foundation in Data Science, Artificial Intelligence (AI), and Machine Learning (ML), combined with expertise in building and scaling data practices. The ideal candidate will possess strong business acumen, with experience in solution selling and pre-sales. As the Practice Head - Data Science & AI, your key responsibilities will include defining and driving the strategic vision for the Data Science and AI practice, leading and mentoring a high-performing team, collaborating with cross-functional teams to integrate data-driven solutions, and staying updated on industry trends and emerging technologies in AI, ML, and data science. You will also be responsible for establishing frameworks, methodologies, and best practices to scale the data science practice, as well as defining and implementing reusable components and accelerators for efficient solution delivery. Additionally, you will play a crucial role in client engagement and pre-sales activities by supporting business development, engaging in solution selling, and building strong relationships with clients. The ideal candidate for this role should have 12+ years of overall experience, with a minimum of 5 years in leading data science/AI teams. You should have proven experience in setting up or leading a data science or AI practice, a strong hands-on technical background in AI, ML, NLP, predictive analytics, and data engineering, as well as experience with tools and platforms like Python, R, TensorFlow, PyTorch, Azure ML, AWS SageMaker, among others. A strong understanding of data strategy, governance, and architecture, along with demonstrated success in solutioning and pre-sales engagements, is essential. Excellent communication, leadership, and stakeholder management skills are also required for this role.,

The role requires you to design, develop, and maintain complex, high-performance, and scalable MLOps systems that interact with AI models and systems. You will collaborate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to comprehend requirements, define project scope, and ensure alignment with business goals. Your expertise will be crucial in selecting, evaluating, and implementing software technologies, tools, and frameworks within a cloud-native (Azure + AML) environment. Troubleshooting and resolving intricate software issues to ensure optimal performance and reliability when interfacing with AI/ML systems is an essential part of your responsibilities. Additionally, you will contribute to software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery. Your role involves contributing to the development of continuous integration and continuous deployment (CI/CD) pipelines, high-performance data pipelines, storage systems, and data processing solutions. You will drive the integration of GenAI models, such as LLMs and foundation models, into production workflows, including overseeing orchestration and evaluation pipelines. Moreover, you will provide support for edge deployment use cases through model optimization, conversion (e.g., to ONNX, TFLite), and containerization for edge runtimes. Your contribution to creating and maintaining technical documentation, including design specifications, API documentation, data models, data flow diagrams, and user manuals, will be vital for effective communication within the team. **Required Qualifications:** - Bachelor's degree in software engineering/computer science or related discipline - Minimum of 6 years of experience in machine learning operations or software/platform development - Strong familiarity with Azure ML, Azure DevOps, Blob Storage, and containerized model deployments on Azure - Proficiency in programming languages commonly used in AI/ML, such as Python, R, or C++ - Experience with Azure cloud platform, machine learning services, and industry best practices **Preferred Qualifications:** - Experience with machine learning frameworks like TensorFlow, PyTorch, or Keras - Familiarity with version control systems like Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps - Knowledge of containerization technologies such as Docker and Kubernetes, along with infrastructure-as-code tools like Terraform or Azure Resource Manager (ARM) templates - Exposure to Generative AI workflows, including prompt engineering, LLM fine-tuning, or retrieval-augmented generation (RAG) - Understanding of GenAI frameworks like LangChain, LlamaIndex, Hugging Face Transformers, and OpenAI API integration - Experience in deploying optimized models on edge devices using ONNX Runtime, TensorRT, OpenVINO, or TFLite - Hands-on experience with monitoring LLM outputs, feedback loops, or LLMOps best practices - Familiarity with edge inference hardware such as NVIDIA Jetson, Intel Movidius, or ARM Cortex-A/NPU devices This is a permanent position requiring in-person work.,

Were Hiring: Lead AI Engineer Experience:5+ Years Experience Location: Kolkata Company: Decorpot Key Skills & Expertise: * AI Frameworks:TensorFlow, PyTorch, TensorFlow\.js, Hugging Face * 3D Integration:Three.js, Babylon.js, WebGL * Cloud Platforms:AWS (SageMaker, S3), Google Cloud AI, Azure ML * Version Control:Git (GitHub/GitLab) * Collaboration Tools:JIRA, Slack, Trello (Agile workflows) * Testing:Postman (API), Selenium (Web apps) Apply Now: perambhargav.reddy@decorpot.com

Design, develop, deploy ML models for real-world applications Implement, optimize ML pipelines using PySpark & MLflow Structured/ unstructured data using Pandas, NumPy Train models using scikit-learn, TensorFlow, PyTorch. Integrate LLMs Required Candidate profile Strong in Python, ML algorithms, model development, evaluation techniques Exp in PySpark model lifecycle management, MLflow Pandas, NumPy, and Scikit-learn, LLMs (OpenAI, Hugging Face Transformers)

Role & responsibilities ML Engineer Role Summary Implements and operationalizes machine learning models, managing the end-to-end ML lifecycle including training, deployment, and monitoring. Detailed Responsibilities Package and deploy ML models using Azure ML pipelines. Automate retraining and versioning workflows. Build and maintain model scoring APIs and batch inference jobs. Monitor performance and drift in deployed models. Implement CI/CD for ML (MLOps). Optimize resource utilization and performance of ML workloads. Key Skills and Technologies Azure ML, MLflow Python (ML frameworks) AKS (Azure Kubernetes Service) for model hosting CI/CD for ML workflows Model monitoring and alerting Experience and Qualifications 5+ years in ML engineering or MLOps. Experience deploying models to production on Azure. Key Deliverables and Outcomes Automated training and deployment pipelines. Production inference APIs with monitoring dashboards. Model rollback and versioning strategies. KPIs / Measures of Success Deployment success rate. Model latency and performance. Drift detection and remediation timelines. Reporting and Collaboration Reports to AI Architect. Works with Data Scientists, Backend Developers, and DevOps teams. Preferred candidate profile