17 Mlops Pipelines Jobs

As a Backend Developer in Bangalore, India with 6 to 13 years of experience, you will collaborate with the development team to build and maintain scalable, secure, and high-performing back-end systems for SaaS products. Your key responsibilities will include designing and implementing microservices architectures, integrating databases, and ensuring seamless operation of cloud-based systems. Your main tasks will involve designing, developing, and maintaining robust and scalable back-end solutions using modern frameworks and tools. You will create, manage, and optimize microservices architectures to ensure efficient communication between services. Additionally, you will develop and integrate RESTful APIs to support front-end and third-party systems. Furthermore, you will be responsible for designing and implementing database schemas, optimizing performance for both SQL and NoSQL databases. Supporting deployment processes by aligning back-end development with CI/CD pipeline requirements and implementing security best practices such as authentication, authorization, and data protection are also crucial aspects of the role. Collaborating with front-end developers to ensure seamless integration of back-end services, monitoring and enhancing application performance, scalability, and reliability, as well as staying up-to-date with emerging technologies and industry trends to improve back-end systems are important responsibilities. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, along with proven experience as a Back-End Developer. Expertise in modern frameworks such as Node.js, Express.js, or Django, proficiency in building and consuming RESTful APIs, and strong database design and management skills with both SQL and NoSQL databases are required. Hands-on experience with microservices architecture, containerization tools like Docker and Kubernetes, cloud platforms like Microsoft Azure, AWS, or Google Cloud, and security best practices are essential. Experience with CI/CD pipelines, Agile methodologies, time-series databases, monitoring solutions, real-time data processing frameworks, serverless architecture, business intelligence tools, API management platforms, AI/ML integration, MLOps pipelines, and iPaaS is a plus. Competencies and attributes that will set you up for success in this role include strong problem-solving and analytical skills, exceptional organizational skills, adaptability to evolving technologies, excellent collaboration and communication skills, and the ability to thrive in self-organizing teams with a focus on transparency and trust.,

As a member of our team at Regal Rexnord, you will be responsible for designing and deploying advanced Generative AI solutions utilizing LLMs, multi-agent systems, and RAG architectures. Your role will involve building scalable and secure applications that integrate FastAPI, React/Streamlit, PostgreSQL, and vector databases. You will have the opportunity to leverage frameworks such as LangChain, CrewAI, and HuggingFace to orchestrate multi-step GenAI workflows efficiently. In this position, you will play a crucial role in implementing prompt engineering, fine-tuning, and performance monitoring to enhance model accuracy and reliability. Collaboration across teams to integrate GenAI features into enterprise platforms and deliver business value will be a key aspect of your responsibilities. Additionally, you will work on optimizing GenAI workloads using cloud-native services on Azure, including OpenAI, Functions, and Fabric. At Regal Rexnord, we prioritize model governance, responsible AI practices, and continuous improvement through robust MLOps pipelines. Our company is a publicly held global industrial manufacturer with 30,000 associates worldwide who are dedicated to providing sustainable solutions that power, transmit, and control motion. Our electric motors and air moving subsystems play a crucial role in creating motion, while our portfolio of highly engineered power transmission components efficiently transmits motion for various industrial applications. Our automation offering, which includes controls, actuators, drives, and precision motors, controls motion across a wide range of applications from factory automation to precision control in surgical tools. Regal Rexnord operates in end markets such as factory automation, food & beverage, aerospace, medical, data center, warehouse, alternative energy, residential and commercial buildings, general industrial, construction, metals and mining, and agriculture. As part of our company, you will be part of three operating segments: Industrial Powertrain Solutions, Power Efficiency Solutions, and Automation & Motion Control. With offices and manufacturing, sales, and service facilities worldwide, we are committed to creating a better tomorrow through sustainable solutions. For more information about our company and our Sustainability Report, please visit RegalRexnord.com.,

About the Role: 13 Job Description: We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks : LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. What's In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology-the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We're constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference. For more information on benefits by country visit: Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority - Ratings - (Strategic Workforce Planning)

The ideal candidate for the position should have a Master's degree in Computer Science, Data Science, or a related field, with a preference for a Ph.D. They should have 8-12 years of experience in a Data Scientist or equivalent role, including at least 4 years of specialized experience in Generative AI. This experience should involve leading technical development, mentoring teams, and troubleshooting and debugging GenAI models in production. Additionally, candidates should have experience working with financial data, applying NLP techniques, developing and testing Python code for GenAI solutions, integrating with vector databases, and monitoring MLOps pipelines. It is essential for the candidate to stay up-to-date with the rapidly evolving GenAI landscape, continuously learn new tools and techniques, and communicate technical concepts clearly to non-technical stakeholders. Candidates must possess demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation, including deploying, monitoring, and maintaining models in a live environment. Proof-of-concept work alone is not sufficient. Candidates should have expertise in various technical areas such as data structures, algorithms, object-oriented programming, scientific computing (NumPy, Pandas, SciPy), machine learning (Scikit-learn, XGBoost, LightGBM), deep learning (TensorFlow, PyTorch), and GenAI (Transformers, LangChain). Specific skills in LLM architectures, RAG, Advanced Chatbot Architectures, Prompt Engineering, Fine-tuning LLMs, and API Development are required. Expert-level Python skills are mandatory, including proficiency in core Python and key libraries for AI/ML and GenAI applications. The candidate should have proven abilities in designing, developing, and deploying complex GenAI projects, a deep understanding of LLMs, RAG, and advanced chatbot architectures, and experience in designing scalable API architectures for GenAI applications. Preferred qualifications include experience with MLOps, cloud computing platforms, conversational AI solutions, research contributions in Generative AI, and building and managing large datasets for training GenAI models. Strong technical leadership, mentorship skills, and excellent communication and collaboration skills are also essential for this role. Overall, the candidate should be able to articulate the challenges and successes of deploying GenAI solutions at scale, effectively convey technical concepts to diverse audiences, and work collaboratively with stakeholders to meet their needs.,

The Director of AI & Computer Vision at GalaxEye will play a crucial role in spearheading artificial intelligence and computer vision initiatives within the company. Your primary responsibility will involve developing cutting-edge algorithms that aim to extract actionable intelligence from satellite imagery. By creating innovative AI & CV algorithms from scratch or modifying existing models, you will contribute to positioning the company as a leader in space-based AI applications. In this leadership role, you will lead the research and development of foundation models tailored specifically for satellite image analysis and geospatial applications. Additionally, you will be tasked with designing and implementing robust MLOPS pipelines to facilitate continuous model enhancement and seamless deployment. Your role will also involve mentoring and guiding a team of AI & CV engineers to execute the technical roadmap and deliver groundbreaking solutions. Regular communication with stakeholders will be essential, as you will conduct monthly reviews to update them on progress, results, and strategic insights. Furthermore, you will have the opportunity to showcase GalaxEye's innovations by publishing research papers and representing the company at prominent AI/CV conferences through presentations, panel participation, and networking. To excel in this role, you should possess a minimum of 5 years of experience in developing, training, and deploying advanced AI models, with a preference for foundation models designed for large-scale computer vision tasks. Demonstrated leadership skills in managing AI R&D teams focused on scalable model development and deployment are crucial. A strong track record of publishing papers in reputable conferences and contributing novel research to the AI/CV domain is highly valued. Deep familiarity with machine learning frameworks and model optimization, as well as excellent communication skills, are essential for success in this position. Prior experience in developing AI models for satellite imagery and geospatial analytics would be advantageous and considered a plus. By fostering a culture of innovation and continuous learning within the team, you will play a key role in driving forward GalaxEye's AI and computer vision initiatives.,

As an AI Engineer passionate about Generative AI and AI-assisted modernization, you will be responsible for developing cutting-edge solutions to drive innovation within the organization. Your primary focus will be on designing and developing in-house GenAI applications, collaborating with vendors to implement proof of concepts (POCs) for complex AI solutions, and aiding in the modernization of legacy systems through AI-driven automation. Your key responsibilities will include: - Designing and developing in-house GenAI applications tailored to internal use cases. - Collaborating with vendors to evaluate and implement POCs for advanced AI solutions. - Working on AI-powered tools to modernize Software Development Life Cycle (SDLC) and migrate code from legacy to modern technologies. - Providing technical support, training, and AI adoption strategies for internal users and teams. - Assisting in integrating AI solutions into software development processes. To excel in this role, you must have: - A Bachelor's or Master's degree in Computer Science, Computer Engineering, Computer Applications, Information Technology, or a related field in AI/ML. - Relevant certification in AI/ML would be advantageous. - Experience with at least 2 successful AI/ML POCs or production deployments. - Previous involvement in AI-powered automation, AI-based DevOps, or AI-assisted coding. - Demonstrated teamwork and delivery capabilities. - Strong analytical and problem-solving skills with a continuous learning mindset. - A positive attitude with attention to detail. In terms of AI/ML expertise, you should possess: - Proficiency in Python programming. - Hands-on experience with GenAI models and Large Language Models (LLMs/SLMs) in real projects or POCs. - Practical experience in Machine Learning and Deep Learning. - Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face. - Understanding of MLOps pipelines and AI model deployment. Additionally, familiarity with System Modernization & Enterprise Technologies is beneficial: - Basic knowledge of Java, Spring, React, Kotlin, and Groovy. - Willingness to work on AI-driven migration projects like PL/SQL to Emery or JavaScript to Groovy DSL. - Experience with code quality, AI-assisted code refactoring, and testing frameworks. For Enterprise integration & AI adoption, you should have: - The ability to integrate AI solutions into enterprise workflows. - Experience with API development and AI model integration in applications. - Proficiency in version control and collaboration tools like Git and CI/CD pipelines. While not mandatory, the following would be considered advantageous: - Experience in code migration and modernization projects. - Exposure to third-party AI tools and their adoption in enterprises. - AI-driven development experience for large-scale software applications.,

You should have a Bachelors or Masters degree in Computer Science, Computer Engineering, Computer Applications, Information Technology, or a related field in AI/ML. Possessing a relevant certification in AI/ML will be considered advantageous. You must have a minimum of 2 successful AI/ML Proof of Concepts (POCs) or production deployments. Previous experience in AI-powered automation, AI-based DevOps, or AI-assisted coding is preferred. Your background should demonstrate a proven track record of teamwork, timely delivery, and problem-solving abilities. Strong analytical skills with a learning mindset are essential for this role. A positive attitude, attention to detail, and the ability to work collaboratively are key qualities we value. In terms of AI/ML expertise, you must have hands-on experience in Python programming and familiarity with GenAI models and LLMs/SLMs through real projects or POCs. Additionally, practical experience in Machine Learning and Deep Learning is required. Proficiency in working with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face is expected. Understanding of MLOps pipelines and AI model deployment processes is a plus. This is a full-time position that requires working during the day shift in person at the specified location.,

You are looking for a DevOps Technical Lead who will play a crucial role in leading the development of an Infrastructure Agent powered by Generative AI (GenAI) technology. In this role, you will be responsible for designing and implementing an intelligent Infra Agent that can handle provisioning, configuration, observability, and self-healing autonomously. Your key responsibilities will include leading the architecture and design of the Infra Agent, integrating various automation frameworks to enhance DevOps workflows, automating infrastructure provisioning and incident remediation, developing reusable components and frameworks using Infrastructure as Code (IaC) tools, and collaborating with AI/ML engineers and SREs to create intelligent infrastructure decision-making logic. You will also be expected to implement secure and scalable infrastructure on cloud platforms such as AWS, Azure, and GCP, continuously improve agent performance through feedback loops, telemetry, and model fine-tuning, drive DevSecOps best practices, compliance, and observability, as well as mentor DevOps engineers and work closely with cross-functional teams. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, along with at least 8 years of experience in DevOps, SRE, or Infrastructure Engineering. You must have proven experience in leading infrastructure automation projects, expertise with cloud platforms like AWS, Azure, GCP, and deep knowledge of tools such as Terraform, Kubernetes, Helm, Docker, Jenkins, and GitOps. Hands-on experience with LLMs/GenAI APIs, familiarity with automation frameworks, and proficiency in programming/scripting languages like Python, Go, or Bash are also required. Preferred qualifications for this role include experience in building or fine-tuning LLM-based agents, contributions to open-source GenAI or DevOps projects, understanding of MLOps pipelines and AI infrastructure, and certifications in DevOps, cloud, or AI technologies.,

As an MLOps Engineer at our Bangalore location, you will play a pivotal role in designing, developing, and maintaining robust MLOps pipelines for generative AI models on AWS. With a Bachelor's or Master's degree in Computer Science, Data Science, or a related field, you should have at least 2 years of proven experience in building and managing MLOps pipelines, preferably in a cloud environment like AWS. Your responsibilities will include implementing CI/CD pipelines to automate model training, testing, and deployment workflows. You should have a strong grasp of containerization technologies such as Docker, container orchestration platforms, and AWS services like SageMaker, Bedrock, EC2, S3, Lambda, and CloudWatch. Practical knowledge of CI/CD principles and tools, along with experience working with large language models, will be essential for success in this role. Additionally, your role will involve driving technical discussions, explaining options to both technical and non-technical audiences, and ensuring software product cost monitoring and optimization. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow, familiarity with generative AI models, and experience with infrastructure-as-code tools like Terraform or CloudFormation will be advantageous. Moreover, knowledge of model monitoring and explainability techniques, various data storage and processing technologies, and experience with other cloud platforms like GCP will further enhance your capabilities. Any contributions to open-source projects related to MLOps or machine learning will be a valuable asset. At CGI, we believe in ownership, teamwork, respect, and belonging. Your work as an MLOps Engineer will focus on turning meaningful insights into action, with opportunities to develop innovative solutions, build relationships with teammates and clients, and access global capabilities to scale your ideas. Join us in shaping your career at one of the largest IT and business consulting services firms globally.,

You are a highly skilled and motivated Senior Machine Learning Engineer with over 5 years of experience in ML model development, MLOps pipelines, Python programming, and hands-on exposure to Generative AI technologies. In this role, you will play a key role in designing, developing, and deploying scalable machine learning models and production-grade AI solutions in a collaborative, fast-paced environment. Your responsibilities will include developing and implementing ML models across various domains such as predictive modeling, NLP, and computer vision. You will also be responsible for building and maintaining end-to-end MLOps pipelines for scalable model training, validation, deployment, and monitoring. Working with GenAI frameworks like LangChain, LlamaIndex, or Hugging Face Transformers for building advanced solutions will be a crucial part of your role. Collaboration with data scientists, data engineers, and DevOps teams to operationalize ML solutions is essential. You will need to write clean, efficient, and well-documented Python code for data preprocessing, feature engineering, and model building. Evaluating model performance, iterative improvements based on experimentation and business feedback, ensuring solutions meet performance, reliability, and scalability requirements, participating in code reviews, sprint planning, and design discussions are all key aspects of this role. To be successful in this position, you should have 5+ years of hands-on experience in Machine Learning and Model Development. Strong proficiency in Python and related ML libraries such as scikit-learn, PyTorch, TensorFlow, Pandas, NumPy is required. Experience with MLOps tools like MLflow, Airflow, Kubeflow, SageMaker, or similar is essential. You should have a solid understanding of Generative AI techniques and experience deploying ML models using containerization (Docker), cloud platforms (AWS/GCP/Azure), and CI/CD workflows. Familiarity with version control (Git), agile methodologies, and collaborative development environments is necessary. Excellent problem-solving, debugging, and analytical skills are crucial for this role. Strong communication and collaboration abilities, comfortable working in a hybrid and globally distributed team, are also required. Nice to have skills include experience with LLMOps and tools like Weights & Biases, VectorDBs (e.g., FAISS, Pinecone, Chroma), a background in software engineering or DevOps, exposure to front-end integration for AI applications (e.g., Streamlit, Gradio), and previous experience working in a late-shift or client-aligned shift model. The shift timings for this role are 2:00 PM to 11:00 PM IST (Hybrid Model 2-3 days onsite per week in Chennai office).,

We are seeking a highly skilled AI/ML Engineer to join our team. As an AI/ML Engineer, you will be responsible for designing, implementing, and optimizing machine learning solutions, encompassing traditional models, deep learning architectures, and generative AI systems. Your role will involve collaborating with data engineers and cross-functional teams to create scalable, ethical, and high-performance AI/ML solutions that contribute to business growth. Your key responsibilities will include developing, implementing, and optimizing AI/ML models using both traditional machine learning and deep learning techniques. You will also design and deploy generative AI models for innovative business applications, in addition to working closely with data engineers to establish and maintain high-quality data pipelines and preprocessing workflows. Integrating responsible AI practices to ensure ethical, explainable, and unbiased model behavior will be a crucial aspect of your role. Furthermore, you will be expected to develop and maintain MLOps workflows to streamline training, deployment, monitoring, and continuous integration of ML models. Your expertise will be essential in optimizing large language models (LLMs) for efficient inference, memory usage, and performance. Collaboration with product managers, data scientists, and engineering teams to seamlessly integrate AI/ML into core business processes will also be part of your responsibilities. Rigorous testing, validation, and benchmarking of models to ensure accuracy, reliability, and robustness are essential aspects of this role. To be successful in this position, you must possess a strong foundation in machine learning, deep learning, and statistical modeling techniques. Hands-on experience with TensorFlow, PyTorch, scikit-learn, or similar ML frameworks is required. Proficiency in Python and ML engineering tools such as MLflow, Kubeflow, or SageMaker is also necessary. Experience in deploying generative AI solutions, understanding responsible AI concepts, solid experience with MLOps pipelines, and proficiency in optimizing transformer models or LLMs for production workloads are key qualifications for this role. Additionally, familiarity with cloud services (AWS, GCP, Azure), containerized deployments (Docker, Kubernetes), as well as excellent problem-solving and communication skills are essential. Ability to work collaboratively with cross-functional teams is also a crucial requirement. Preferred qualifications include experience with data versioning tools like DVC or LakeFS, exposure to vector databases and retrieval-augmented generation (RAG) pipelines, knowledge of prompt engineering, fine-tuning, and quantization techniques for LLMs, familiarity with Agile workflows and sprint-based delivery, and contributions to open-source AI/ML projects or published papers in conferences/journals. Join our team at Lucent Innovation, an India-based IT solutions provider, and enjoy a work environment that promotes work-life balance. With a focus on employee well-being, we offer 5-day workweeks, flexible working hours, and a range of indoor/outdoor activities, employee trips, and celebratory events throughout the year. At Lucent Innovation, we value our employees" growth and success, providing in-house training, as well as quarterly and yearly rewards and appreciation. Perks: - 5-day workweeks - Flexible working hours - No hidden policies - Friendly working environment - In-house training - Quarterly and yearly rewards & appreciation,

As an AI/ML Specialist, you will be responsible for building intelligent systems utilizing OT sensor data and Azure ML tools. Your primary focus will be collaborating with data scientists, engineers, and operations teams to develop scalable AI solutions addressing critical manufacturing issues such as predictive maintenance, process optimization, and anomaly detection. This role involves bridging the edge and cloud environments by deploying AI solutions to run effectively on either cloud platforms or industrial edge devices. Your key functions will include designing and developing ML models using time-series sensor data from OT systems, working closely with engineering and data science teams to translate manufacturing challenges into AI use cases, implementing MLOps pipelines on Azure ML, and integrating with Databricks/Delta Lake. Additionally, you will be responsible for deploying and monitoring models at the edge using Azure IoT Edge, conducting model validation, retraining, and performance monitoring, as well as collaborating with plant operations to contextualize insights and integrate them into workflows. To qualify for this role, you should have a minimum of 5 years of experience in machine learning and AI. Hands-on experience with Azure ML, ML flow, Databricks, and PyTorch/TensorFlow is essential. You should also possess a proven ability to work with OT sensor data such as temperature, vibration, flow, etc. A strong background in time-series modeling, edge inferencing, and MLOps is required, along with familiarity with manufacturing KPIs and predictive modeling use cases.,

As a Senior Data Scientist specializing in Generative AI at our organization, you will play a crucial role in driving technical innovation and delivering impactful results within a team setting. You will be responsible for working with financial data, applying NLP techniques, refining prompt engineering strategies for LLMs, collaborating with stakeholders, developing and testing Python code for GenAI solutions, integrating with vector databases, monitoring MLOps pipelines, researching emerging GenAI technologies, and troubleshooting and debugging GenAI models in production. To excel in this role, you must possess a Master's degree in Computer Science, Data Science, or a related field, with a Ph.D. being preferred. You should have 8-12 years of experience in a Data Scientist or equivalent role, with at least 4 years of specialized experience in Generative AI. Additionally, you should have demonstrable experience in the full lifecycle of real-world, production-level GenAI project implementation. You must stay up-to-date with the rapidly evolving GenAI landscape, continuously learn and explore new tools and techniques, and effectively communicate technical concepts to non-technical stakeholders. Proficiency in Python, along with expertise in key libraries for AI/ML and GenAI applications such as TensorFlow, PyTorch, and Transformers, is mandatory. Experience in designing and implementing scalable API architectures for GenAI applications, along with a deep understanding of Machine Learning concepts, is essential. Preferred qualifications for this role include experience with MLOps, cloud computing platforms, conversational AI solutions, and contributions to research and publications in the field of Generative AI. As a Senior Data Scientist, you will be expected to demonstrate strong technical leadership and mentorship skills, as well as excellent communication and collaboration abilities. This job description provides a comprehensive overview of the responsibilities and qualifications required for the Senior Data Scientist position. If you are a highly motivated individual with a strong passion for Generative AI and possess the necessary technical skills and experience, we encourage you to apply for this role.,

You are an experienced Solution Architect with a solid background in software architecture and a good understanding of AI-based products and platforms. Your main responsibility will be to design robust, scalable, and secure architectures that support AI-driven applications and enterprise systems. In this role, you will collaborate closely with cross-functional teams, including data scientists, product managers, and engineering leads, to ensure the alignment of business needs, technical feasibility, and AI capabilities. Your key responsibilities will include architecting end-to-end solutions for enterprise and product-driven platforms, such as data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. You will guide teams in selecting appropriate technologies, tools, and design patterns for building scalable systems. Additionally, you will work with AI/ML teams to understand model requirements and facilitate their smooth deployment and integration into production environments. In this role, you will define system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. Furthermore, you will collaborate with stakeholders to translate business requirements into technical solutions, emphasizing scalability, performance, and security. Your leadership will be crucial in promoting best practices for software development, DevOps, and cloud-native architecture. You will also conduct architecture reviews to ensure compliance with security, performance, and regulatory standards. To be successful in this role, you should have at least 10 years of experience in software architecture or solution design roles. You should demonstrate expertise in designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. Hands-on experience with major cloud providers like AWS, GCP, or Azure is essential. Familiarity with AI/ML platforms and components, data architectures, containerization, DevOps principles, and the ability to lead technical discussions are also required skills. Preferred qualifications include exposure to AI model lifecycle management, infrastructure-as-code tools like Terraform or Pulumi, knowledge of GraphQL, gRPC, or serverless architectures, and previous experience in AI-driven product companies or digital transformation programs. In return, you will have the opportunity to play a high-impact role in designing intelligent systems that drive the future of AI adoption. You will work alongside forward-thinking engineers, researchers, and innovators, with a strong focus on career growth, learning, and technical leadership. The compensation offered is competitive and reflective of the value you bring to the role.,

Job Title: Senior Generative AI Developer (Lead - Data Science) Gurgaon / Noida | 7-10 Years Experience About the Role We are looking for an experienced Senior Generative AI Developer to lead the design, development, and deployment of large-scale enterprise-grade GenAI systems. This is a hybrid role requiring both deep hands-on expertise and strategic leadership , working across multi-cloud environments and managing the full lifecycle of AI/ML systems. Key Responsibilities Technical Leadership Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for performance-cost optimization. Design and scale training pipelines using FSDP, DeepSpeed on GPU/TPU clusters. Cloud-Native AI Development Build and manage multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps. Implement enterprise-grade security: VPC peering, private endpoints , and regulatory compliance (e.g., data residency). Innovation & Strategy Drive pioneering initiatives such as Agentic workflows , real-time fine-tuning, and synthetic data generation . Define and execute AI governance : model cards, drift monitoring, red-teaming protocols. Cross-Functional Impact Collaborate with product and business teams to define GenAI strategy and ROI metrics (e.g., automation cost savings). Mentor junior engineers and promote GenAI best practices across the organization. Required Qualifications Education : Bachelors/Master’s in CS, AI/ML, or equivalent experience. Experience : 5+ years in ML, 2+ years specifically in Generative AI. Technical Mastery Languages : Expert in Python Frameworks : PyTorch, TensorFlow Extended (TFX), ONNX Runtime Certifications : Azure AI Engineer Expert, GCP ML Engineer (preferred) GenAI Expertise Experience shipping production-scale GenAI systems (e.g., 10k+ QPS chatbots, GitHub Copilot-scale models). Mastery of advanced LLM techniques (LLM orchestration, guardrails, self-reflective prompting). Must-Have Experience Azure : Azure OpenAI, MLOps Pipelines, Cognitive Search GCP : Vertex AI Evaluation, Gemini Multimodal, TPU v5 Pods Built RAG systems using hybrid search (vector + keyword) and real-time data hydration Led AI compliance in regulated domains (finance, healthcare) Preferred Additions Experience with multi-cloud GenAI deployments (e.g., training on GCP, serving on Azure). Certification in Azure and/or GCP AI tracks. Exposure to autonomous agents, vector databases , and AI-driven business automation.

The Opportunity Are you passionate about building intelligent, enterprise-grade AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic frameworks? At Nutanix, we're looking for a skilled and experienced AI/ML engineer to help shape the future of generative AI within our SaaS Engineering organization. As a senior member of our team, youll work at the cutting edge of AI innovationdeveloping and deploying state-of-the-art LLMs and embedding models, optimizing model performance, and building scalable ML pipelines with real-world impact. About the Team At Nutanix, you will be joining a dynamic central platform team that plays a pivotal role in revolutionizing our approach to artificial intelligence and machine learning within the SaaS Engineering group. Comprising eight experienced engineers, our team specializes in addressing the GenAI, machine learning, and data science needs of various squads within the organization. Our diverse skill set ensures we collaborate effectively to create innovative solutions, leveraging the latest advancements in technology to drive our initiatives forward. Your Role Design and deploy Retrieval-Augmented Generation (RAG) pipelines . Build, fine-tune, and deploy LLMs and embedding models such as LLaMA 3 , Gemma , Mistral , and other domain-specific transformers. Fine-tune both LLMs and embedding models for specialized enterprise tasks including Q&A, summarization, classification, and conversational AI. Develop and maintain agentic frameworks capable of orchestrating task-specific intelligent agents with memory, planning, and tool-use capabilities. Build and evaluate custom agents for use cases like document analysis, data querying, and interactive user support. Implement evaluation frameworks for LLM outputs, including both automated metrics and task-specific success criteria. Work closely with data engineering teams to develop custom training pipelines and extract meaningful insights from large-scale internal datasets. Develop MLOps pipelines for training, deployment, and monitoring using tools like MLflow , Kubeflow , and custom CI/CD workflows. Deploy optimized inference endpoints for high-performance, low-latency model serving at scale. Manage vectorization workflows using advanced embedding models and vector databases for semantic search and content retrieval. Demonstrate working knowledge of LangChain, OpenAI function-calling, vector databases and scalable retrieval logic. Work with Kubernetes clusters to provision, scale, and monitor AI/ML workloads; understand GPU, CPU, and storage hardware requirements for efficient deployment. Collaborate with cross-functional teams including backend, data, and infrastructure engineers to integrate models seamlessly into production systems. What You Will Bring Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Applied Math, or a related field. 5+ years of hands-on experience building, deploying, and maintaining AI/ML systems in production environments. Strong foundation in MLOps, including model versioning, CI/CD, monitoring, and retraining workflows. In-depth understanding of Kubernetes (K8s) and GPU-based infrastructure, including container orchestration and GPU scheduling for AI workloads. Experience working with Elasticsearch for semantic search and integrating it within RAG or LLM-driven architectures. Proficient in Python (core ML libraries like PyTorch, Pandas, and NumPy). Hands-on experience using Jupyter Notebooks for experimentation, documentation, and collaboration. Comfortable with Unix-based systems, shell scripting, and command-line tooling for ML operations and debugging. Familiarity with LangChain, LLM orchestration, and vector database integration. Strong collaboration and communication skills, with the ability to mentor junior team members and drive initiatives independently. Open-source contributions or published work in the ML/AI domain is a plus.

As our AI Developer, you wont just write codeyoull partner with AI tools to conceptualize, prototype, and build full-stack features in record time. You'll convert user needs and contract workflows into functioning, AI-driven softwareend to end. This role bridges software engineering, product execution, and AI-engineeringthere is no separation between front-end, back-end, and model integration: you do it all. Key Responsibilities Use tools like Windsurf, Cursor, GitHub Copilot, etc., to accelerate development of full-stack features. Design, prototype, test, and deploy CLM modules: clause extraction, contract review UI, workflow automation. Integrate LLMs, vector embeddings, rule engines, and APIs for tasks like clause summarization, risk detection, redlining. Collaborate closely with product, legal/contract experts, and UX to translate business needs into AI-first applications. Optimize for scalability, security, and reliability in production environments. Continuously evaluate and adopt emerging AI tools and best practices, including prompt engineering, new assistive coding workflows, and MLOps pipelines (X-Team). Ensure ethical and privacy-compliant AIbias detection, data protection, and auditability are built-in (Wikipedia)