167 Kubeflow Jobs

You should possess a minimum of 7-10 years of industry experience, out of which a minimum of 5 years should have been in machine learning roles. Your proficiency in Python and popular ML libraries such as TensorFlow, PyTorch, and Scikit-learn should be advanced. Furthermore, you should have hands-on experience in distributed training, model optimization including quantization and pruning, and inference at scale. Experience with cloud ML platforms like AWS (SageMaker), GCP (Vertex AI), or Azure ML is essential. It is expected that you are familiar with MLOps tooling such as MLflow, TFX, Airflow, or Kubeflow, and data engineering frameworks like Spark, dbt, or Apache Beam. A solid understanding of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay) is crucial for this role. In addition to technical skills, problem-solving abilities, effective communication, and strong documentation skills are highly valued in this position.,

You are a highly skilled and motivated Technical Lead who will be joining our growing team. Your role will involve leading and delivering complex technical projects in areas such as AI/ML, Full Stack Development, and Cloud-based solutions. Your responsibilities will include overseeing the end-to-end execution of multiple software development projects, focusing on AI/ML initiatives and products to ensure timely delivery and high quality. You will be responsible for architecture design, technical planning, and code quality across the team, specifically for scalable AI/ML solutions, robust data pipelines, and integration of models into production systems. Collaboration with stakeholders, both internal and external, will be a key part of your role. You will gather requirements for AI/ML features, provide progress updates, and effectively manage expectations. Mentoring and guiding developers to foster a culture of continuous improvement and technical excellence, especially in AI/ML best practices, model development, and ethical AI considerations, will be essential. You will work closely with cross-functional teams, including QA, DevOps, and UI/UX designers, to seamlessly integrate AI/ML models and applications into broader systems. Implementing best practices in development, deployment, and version control with a strong emphasis on MLOps and reproducible AI/ML workflows is crucial. Tracking project milestones, managing technical risks, and ensuring that AI/ML projects align with overarching business goals will be part of your responsibilities. Participating in client calls to provide technical insights and solution presentations, demonstrating the value and capabilities of our AI/ML offerings, will be required. Driving research, experimentation, and adoption of cutting-edge AI/ML algorithms and techniques to enhance product capabilities is also expected from you. Required Skills: - Strong hands-on experience in at least one Fullstack framework (e.g., MERN stack, Python with React). - Proven experience managing and delivering end-to-end AI/ML projects or products. - Proficiency in major AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn. - Solid experience with data processing, feature engineering, and data pipeline construction for machine learning workloads. - Proficiency in project tracking tools like Jira, Trello, or Asana. - Solid understanding of SDLC, Agile methodologies, and CI/CD practices. - Strong knowledge of cloud platforms like AWS, Azure, or GCP, especially their AI/ML services. - Excellent problem-solving, communication, and leadership skills. Preferred Qualifications: - Bachelor's or Master's degree in a related field. - Experience with containerization technologies and microservices architecture. - Exposure to MLOps practices and tools. - Prior experience in a client-facing technical leadership role. - Familiarity with big data technologies. - Contributions to open-source AI/ML projects or relevant publications are a plus. (ref:hirist.tech),

????Were Hiring: ML Ops / Data Engineer (Minimum 5 Years Experience)??? Are you a data engineering professional withat least 5 years of experiencein building scalable data pipelines and deploying machine learning models Were looking for a talentedML Ops / Data Engineerto join our team inNoida! ????What Youll Do: Design and maintain robust data pipelines for large-scale datasets Collaborate with data scientists to deploy and monitor ML models in production Develop and optimize ETL processes usingAWS Glue,PySpark, andSQL Automate ML workflows using tools likeKubeflow,MLflow, orTFX Ensure model versioning, logging, and performance tracking Work with cloud platforms (AWS preferred) and modern data storage solutions Ensure data security, integrity, and compliance ?????Must-Have Skills: Minimum 5 years of experiencein data engineering or ML Ops Proficiency inAWS Services(Lambda, EventBridge, Fargate) Strong knowledge ofSQL,Docker, andKubernetes Experience withAWS Glue,PySpark, and containerized environments ????Location:Noida ????Employment Type:Permanent ????Primary Skill:AWS Cloud, ML Ops, Data Engineering If you&aposre ready to take your career to the next level and work on cutting-edge ML infrastructure, wed love to connect! #Hiring #MLOps #DataEngineering #AWSJobs #ETL #MachineLearning #NoidaJobs #TechCareers #DataPipelines #5YearsExperience Show more Show less

Job Summary Liaising with coworkers and clients to elucidate the requirements for each task. Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed. Reformulating existing frameworks to optimize their functioning. Testing such structures to ensure that they are fit for use. Preparing raw data for manipulation by data scientists. Detecting and correcting errors in your work. Ensuring that your work remains backed up and readily accessible to relevant coworkers. Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs. Experience with Azure ADLS, Apache Parquet, Iceberg, Kubeflow and Airflow

You are an experienced Software Engineer specializing in Machine Learning with at least 2+ years of relevant experience. In this role, you will be responsible for designing, developing, and optimizing machine learning solutions and data systems. Your proven track record in implementing ML models, building scalable systems, and collaborating with cross-functional teams will be essential in solving complex challenges using data-driven approaches. As a Software Engineer - Machine Learning, your primary responsibilities will include designing and implementing end-to-end machine learning solutions, building and optimizing scalable data pipelines, collaborating with data scientists and product teams, monitoring and optimizing deployed models, staying updated with the latest trends in machine learning, debugging complex issues related to ML systems, and documenting processes for knowledge sharing and clarity. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related fields. Your technical skills should include a strong proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or scikit-learn, experience with data processing tools like Pandas, NumPy, and Spark, proficiency in SQL and database systems, hands-on experience with cloud platforms (AWS, GCP, Azure), familiarity with CI/CD pipelines and Git, and experience with model deployment frameworks like Flask, FastAPI, or Docker. Additionally, you should possess strong analytical skills, leadership abilities to guide junior team members, and a proactive approach to learning and collaboration. Preferred qualifications include experience with MLOps tools like MLflow, Kubeflow, or SageMaker, knowledge of big data technologies such as Hadoop, Spark, or Kafka, familiarity with advanced ML techniques like NLP, computer vision, or reinforcement learning, and experience in designing and managing streaming data workflows. Key Performance Indicators for this role include successfully delivering optimized and scalable ML solutions within deadlines, maintaining high model performance in production environments, and ensuring seamless integration of ML models with business applications. Join us in this exciting opportunity to drive innovation and make a significant impact in the field of Machine Learning.,

As a Senior Machine Learning Engineer with over 10 years of experience, you will play a crucial role in designing, building, and deploying scalable machine learning systems in production. In this role, you will collaborate closely with data scientists to operationalize models, take ownership of ML pipelines from end to end, and enhance the reliability, automation, and performance of our ML infrastructure. Your primary responsibilities will include designing and constructing robust ML pipelines and services for training, validation, and model deployment. You will work in collaboration with various stakeholders such as data scientists, solution architects, and DevOps engineers to ensure alignment with project goals and requirements. Additionally, you will be responsible for ensuring cloud integration compatibility with AWS and Azure, building reusable infrastructure components following best practices in DevOps and MLOps, and adhering to security standards and regulatory compliance. To excel in this role, you should possess strong programming skills in Python, have deep experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, and be proficient in MLOps tools like MLflow, Airflow, TFX, Kubeflow, or BentoML. Experience in deploying models using Docker and Kubernetes, familiarity with cloud platforms and ML services, and proficiency in data engineering tools are essential for success in this position. Additionally, knowledge of CI/CD, version control, and infrastructure as code along with experience in monitoring/logging tools will be advantageous. Good-to-have skills include experience with feature stores and experiment tracking platforms, knowledge of edge/embedded ML, model quantization, and optimization, as well as familiarity with model governance, security, and compliance in ML systems. Exposure to on-device ML or streaming ML use cases and experience in leading cross-functional initiatives or mentoring junior engineers will also be beneficial. Joining Ericsson will provide you with an exceptional opportunity to leverage your skills and creativity to address some of the world's toughest challenges. You will be part of a diverse team of innovators who are committed to pushing the boundaries of innovation and crafting groundbreaking solutions. As a member of this team, you will be challenged to think beyond conventional limits and contribute to shaping the future of technology.,

You should have at least 2-7 years of experience in software engineering and ML development. Proficiency in Python and ML libraries like Scikit-learn, TensorFlow, or PyTorch is essential. Your responsibilities will include building and evaluating models, data preprocessing, and feature engineering. It is important to have a good understanding of REST APIs, Docker, Git, and CI/CD tools. A strong foundation in software engineering principles such as data structures, algorithms, and design patterns is required. Hands-on experience with MLOps platforms like MLflow, TFX, Airflow, and Kubeflow is preferred. Exposure to NLP, large language models (LLMs), or computer vision projects will be beneficial for this role. Experience with cloud platforms such as AWS, GCP, and Azure, as well as managed ML services, is a plus. Any contributions to open-source ML libraries or participation in ML competitions like Kaggle or DrivenData will be considered an advantage.,

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

You are a talented and driven Machine Learning Engineer with 2-5 years of experience, looking to join a dynamic team in Chennai. Your expertise lies in machine learning principles and hands-on experience in building, deploying, and managing ML models in production environments. In this role, you will focus on MLOps practices and orchestration to ensure robust, scalable, and automated ML pipelines. Your responsibilities will include designing, developing, and implementing end-to-end MLOps pipelines for deploying, monitoring, and managing machine learning models in production. You will use orchestration tools such as Apache Airflow, Kubeflow, AWS Step Functions, or Azure Data Factory to automate ML workflows. Implementing CI/CD practices for ML code, models, and infrastructure will be crucial for ensuring rapid and reliable releases. You will also establish monitoring and alerting systems for deployed ML models, optimize performance, troubleshoot and debug issues across the ML lifecycle, and create and maintain technical documentation. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field, along with 2-5 years of professional experience as a Machine Learning Engineer or MLOps Engineer. Your skills should include proficiency in Python and its ML ecosystem, hands-on experience with major cloud platforms and their ML/MLOps services, knowledge of orchestration tools, containerization technologies, CI/CD pipelines, and database systems. Strong problem-solving, analytical, and communication skills are essential for collaborating effectively with Data Scientists, Data Engineers, and Software Developers in an Agile environment.,

???? About Es Magico Es Magico is an AI-first enterprise transformation organisation that goes beyond consulting we deliver scalable execution across sectors such as BFSI, Healthcare, Entertainment, and Education. With offices in Mumbai and Bengaluru, our mission is to augment the human workforce by deploying bespoke AI employees across business functions, innovating swiftly and executing with trust. We also partner with early-stage startups as a venture builder, transforming 0 ? 1 ideas into AI-native, scalable products. ???? Role: MLOps Engineer ??? Location: Bengaluru (Hybrid) ??? Experience: 14 years ??? Joining: Immediate ???? Key Responsibilities Design, develop, and maintain scalable ML pipelines for training, testing, and deployment. Automate model deployment, monitoring, and version control across dev/staging/prod environments. Integrate CI/CD pipelines for ML models using tools like MLflow, Kubeflow, Airflow, etc. Manage containerized workloads using Docker and orchestrate with Kubernetes or GKE. Collaborate closely with data scientists and product teams to optimize ML model lifecycle. Monitor performance and reliability of deployed models and troubleshoot issues as needed. ????? Technical Skills Experience with MLOps frameworks: MLflow, TFX, Kubeflow, or SageMaker Pipelines. Proficient in Python and common ML libraries (scikit-learn, pandas, etc.). Solid understanding of CI/CD practices and tools (e.g., GitHub Actions, Jenkins, Cloud Build). Familiar with Docker, Kubernetes, and Google Cloud Platform (GCP). Comfortable with data pipeline tools like Airflow, Prefect, or equivalent. ???? Preferred Qualifications 14 years of experience in MLOps, ML engineering, or DevOps with ML workflows. Prior experience with model monitoring, drift detection, and automated retraining. Exposure to data versioning tools like DVC or Delta Lake is a plus. GCP certifications or working knowledge of Vertex AI is a strong advantage. ???? How to Apply Send your resume to [HIDDEN TEXT] with the subject line: Application MLOps Engineer. Show more Show less

About Biz2X Biz2X is the leading digital lending platform, enabling financial providers to power growth with a modern omni-channel experience, best-in-class risk management tools and a comprehensive yet flexible Servicing engine. The company partners with financial institutions to support their Digital Transformation efforts with Biz2Xs digital lending platform. Biz2X solutions not only reduces operational expenses, but accelerates lending growth by significantly improving client experience, reducing total turnaround time, and equipping the relationship managers with powerful monitoring insights and alerts Read Our Latest Press Release : Press Release - Biz 2X Job Overvi ew: We are seeking for a Senior Engineer AI/ML to drive the development and deployment of sophisticated AI solutions in our fintech products. You will oversee MLOps pipelines and manage large language models (LLMs) to enhance our financial technology services. Key Responsibilities: AI/ML Development: Design and implement advanced ML models for applications including fraud detection, credit scoring, and algorithmic trading. MLOps: Develop and manage MLOps pipelines using tools such as MLflow, Kubeflow, and Airflow for CI/CD, model monitoring, and automation. LLMOps: Optimize and operationalize LLMs (e.g., GPT-4, BERT) for fintech applications like automated customer support and sentiment analysis. Collaboration: Work with product managers, data engineers, and business analysts to align technical solutions with business objectives. Qualifications: Experience: 4-6 years in AI, ML, MLOps, and LLMOps with a focus on fintech. Technical Skills: Expertise in TensorFlow, PyTorch, scikit-learn, and MLOps tools (MLflow, Kubeflow). Proficiency in large language models (LLMs) and cloud platforms (AWS, GCP, Azure). Strong programming skills in Python, Java, or Scala. Experience in building RAG pipelines, NLP, OCR and Pyspark Good to have: Production GenAI Experience in Fintech/Lending domain Show more Show less

Company Description About Mirantis Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environmenton-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. Job Description Mirantis is adding a Pre-Sales Solution Architect to our team. As part of our client-facing technical team, you will leverage your technical and consultative expertise to guide clients from their current state to strategic solutions that deliver measurable, real-world business outcomes. You will work in lockstep with the sales team to communicate Mirantis vision, features, and value, and with the services team to ensure that the vision and outcomes are delivered to the client. You will also work with product management, marketing, and engineering teams to understand our product and offerings, and to provide feedback which will define enhancements to our solutions. The Pre-Sales Solution Architect position requires technical thought leadership and offers candidates opportunities for professional growth across a variety of business and technology domains. You will play a key role as an individual leader in the field and contribute internally to an organizational culture that deeply values transparency, performance, development, creativity, collaboration, and trust. Responsibilities Act as a trusted technical advisor and client advocate. Build long-term, value-driven relationships with stakeholders. Understand client goals and architect tailored solutions using Mirantis products and open-source technologies to drive business outcomes. Drive technical wins during sales engagements by demonstrating solution fit, feasibility, and alignment with strategic objectives. Ensure seamless transitions from pre-sales to post-sales with ongoing technical guidance for successful delivery and adoption. Collaborate cross-functionally across Sales, Product, Services, and CTO teams to align on customer qualification, solutioning, and execution. Develop and present custom demos, prototypes, and reference architectures that align with customer use cases. Provide structured field insights and client feedback to support product and services strategy. Stay current with emerging technologies (e.g., Kubernetes, AI/ML) and serve as a knowledge-sharing resource internally and externally. Identify and nurture account and partner growth opportunities, aligning solutions to customer and partner visions. Contribute to strategic account planning and customer success roadmaps to support long-term engagements. Qualifications Required Skills/Abilities Proven experience engaging with senior IT and engineering leadership, including CIOs and CTOs, and aligning technical solutions with strategic priorities. Demonstrated thought leadership through client engagement, public speaking (e.g., conferences, webinars), or community contributions. Strong understanding of the competitive landscape within the cloud infrastructure and open-source ecosystem. Practical knowledge of distributed systems, modern application architectures, software development practices, and DevOps methodologies. Awareness of industry trends, compliance requirements, and regulatory environments, with the ability to assess their impact on client needs. Familiarity with AI/ML infrastructure tools (e.g., Kubeflow, MLflow, NVIDIA AI), and how they integrate with cloud-native platforms. Demonstrated hands-on experience in the following areas: Open-source software stacks Cloud infrastructure including Kubernetes, OpenStack, Docker, microservices, and public cloud services (AWS, GCP, Azure) DevOps and automation tools, including CI/CD pipelines Observability tooling, including open-source monitoring, logging, and alerting systems Experience working effectively in a globally distributed team environment. Qualifications 5+ years of experience in a client-facing technical role such as Sales Engineer, Consultant, or Solutions Architect Four year college degree preferred Excellent written and verbal communication skills, including public speaking and demonstrations Technical certifications (optionally), such as Certified Kubernetes Administrator (CKA), AWS Certified Solutions Architect, or similar industry-recognized credentials. Ability to travel up to 50% Additional Information Why youll love Mirantis Work with an established leader in the cloud infrastructure industry. Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies. Be a part of cutting-edge, open-source innovation. Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued. Receive a competitive compensation package with strong benefits plan. We are a Leader for Container Management in G2 (#2 after AWS)! It is understood that Mirantis, Inc. may use automated decision-making technology (ADMT) for specific employment-related decisions. Opting out of ADMT use is requested for decisions about evaluation and review connected with the specific employment decision for the position applied for. You also have the right to appeal any decisions made by ADMT by sending your request to [HIDDEN TEXT] By submitting your resume, you consent to the processing and storage of your personal data in accordance with applicable data protection laws, for the purposes of considering your application for current and future job opportunities. We are a Leader for Container Management in G2 (#2 after AWS)! We are a Leader for Container Management in G2 (#2 after AWS)! Show more Show less

About the Role We are looking for an experienced DevOps Engineer to join our engineering team. This role involves setting up, managing, and scaling development, staging, and production environments both on AWS cloud and on-premise (open source stack) . You will be responsible for CI/CD pipelines, infrastructure automation, monitoring, container orchestration, and model deployment workflows for our enterprise applications and AI platform. Key Responsibilities Infrastructure Setup & Management Design and implement cloud-native architectures on AWS and be able to manage on-premise open source environments when required . Automate infrastructure provisioning using tools like Terraform or CloudFormation. Maintain scalable environments for dev, staging, and production . CI/CD & Release Management Build and maintain CI/CD pipelines for backend, frontend, and AI workloads. Enable automated testing, security scanning, and artifact deployments. Manage configuration and secret management across environments. Containerization & Orchestration Manage Docker-based containerization and Kubernetes clusters (EKS, self-managed K8s) . Implement service mesh, auto-scaling, and rolling updates. Monitoring, Security, and Reliability Implement observability (logging, metrics, tracing) using open source or cloud tools. Ensure security best practices across infrastructure, pipelines, and deployed services. Troubleshoot incidents, manage disaster recovery, and support high availability. Model DevOps / MLOps Set up pipelines for AI/ML model deployment and monitoring (LLMOps). Support data pipelines, vector databases, and model hosting for AI applications. Required Skills and Qualifications Cloud & Infra Strong expertise in AWS services : EC2, ECS/EKS, S3, IAM, RDS, Lambda, API Gateway, etc. Ability to set up and manage on-premise or hybrid environments using open source tools. DevOps & Automation Hands-on experience with Terraform / CloudFormation . Strong skills in CI/CD tools such as GitHub Actions, Jenkins, GitLab CI/CD, or ArgoCD. Containerization & Orchestration Expertise with Docker and Kubernetes (EKS or self-hosted). Familiarity with Helm charts, service mesh (Istio/Linkerd). Monitoring / Observability Tools Experience with Prometheus, Grafana, ELK/EFK stack, CloudWatch . Knowledge of distributed tracing tools like Jaeger or OpenTelemetry. Security & Compliance Understanding of cloud security best practices . Familiarity with tools like Vault, AWS Secrets Manager. Model DevOps / MLOps Tools (Preferred) Experience with MLflow, Kubeflow, BentoML, Weights & Biases (W&B) . Exposure to vector databases (pgvector, Pinecone) and AI pipeline automation . Preferred Qualifications Knowledge of cost optimization for cloud and hybrid infrastructures . Exposure to infrastructure as code (IaC) best practices and GitOps workflows. Familiarity with serverless and event-driven architectures . Education Bachelors degree in Computer Science, Engineering, or related field (or equivalent experience). What We Offer Opportunity to work on modern cloud-native systems and AI-powered platforms . Exposure to hybrid environments (AWS and open source on-prem). Competitive salary, benefits, and growth-oriented culture. Show more Show less

As a Senior Systems Engineer specializing in Data DevOps/MLOps, you will play a crucial role in our team by leveraging your expertise in data engineering, automation for data pipelines, and operationalizing machine learning models. This position requires a collaborative professional who can design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment. You will be responsible for building and maintaining infrastructure for data processing and model training using cloud-native tools and services. Your role will involve automating processes for data validation, transformation, and workflow orchestration, ensuring seamless integration of ML models into production. You will work closely with data scientists, software engineers, and product teams to optimize performance and reliability of model serving and monitoring solutions. Managing data versioning, lineage tracking, and reproducibility for ML experiments will be part of your responsibilities. You will also identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience. Implementing security measures to safeguard data integrity and ensure regulatory compliance will be crucial, along with diagnosing and resolving issues throughout the data and ML pipeline lifecycle. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field, along with 4+ years of experience in Data DevOps, MLOps, or similar roles. Proficiency in cloud platforms like Azure, AWS, or GCP is required, as well as competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible. Expertise in containerization and orchestration technologies like Docker and Kubernetes is essential, along with a background in data processing frameworks such as Apache Spark or Databricks. Skills in Python programming, including proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch, are necessary. Familiarity with CI/CD tools such as Jenkins, GitLab CI/CD, or GitHub Actions, as well as understanding version control tools like Git and MLOps platforms such as MLflow or Kubeflow, will be valuable. Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana), strong problem-solving skills, and the ability to contribute independently and within a team are also required. Excellent communication skills and attention to documentation are essential for success in this role. Nice-to-have qualifications include knowledge of DataOps practices and tools like Airflow or dbt, an understanding of data governance concepts and platforms like Collibra, and a background in Big Data technologies like Hadoop or Hive. Qualifications in cloud platforms or data engineering would be an added advantage.,

As a Senior AI/ML Engineer/Lead at our company located in Mohali, you will play a crucial role in leading the design, architecture, and delivery of complex AI/ML solutions. With over 8 years of experience, you will be responsible for developing and implementing machine learning models across various domains like NLP, computer vision, recommendation systems, classification, and regression. Your expertise will be utilized to integrate Large Language Models (LLMs) such as GPT, BERT, LLaMA, and other state-of-the-art transformer architectures into our enterprise-grade applications to drive innovation. Your key responsibilities will include selecting and implementing ML frameworks, tools, and cloud technologies that align with our business goals. You will lead AI/ML experimentation, PoCs, benchmarking, and model optimization initiatives while collaborating with data engineering, software development, and product teams to integrate ML capabilities seamlessly into production systems. Additionally, you will establish and enforce robust MLOps pipelines covering CI/CD for ML, model versioning, reproducibility, and monitoring to ensure reliability at scale. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field. Your hands-on experience in the AI/ML domain, along with a proven track record of delivering production-grade ML systems, will be highly valued. Proficiency in machine learning algorithms, deep learning architectures, and advanced neural network design is essential. You should also possess expertise in LLMs, transformer-based models, prompt engineering, and embeddings, with strong programming skills in Python and familiarity with cloud platforms for scalable ML workloads. Having experience with MLOps tools and practices, such as MLflow, Kubeflow, SageMaker, or equivalent, will be beneficial. Furthermore, exposure to vector databases, real-time AI systems, edge AI, streaming data environments, and active contributions to open-source projects, research publications, or thought leadership in AI/ML will be advantageous. A certification in AI/ML would be a significant plus. If you are a self-driven individual with excellent leadership, analytical thinking, and communication skills, and if you are passionate about staying updated on AI advancements and championing their adoption in business use, we encourage you to apply for this exciting opportunity.,

We are seeking a talented Systems Architect (AVP level) with specialized knowledge in designing and expanding Generative AI solutions for production environments. In this pivotal position, you will collaborate across various teams including data scientists, ML engineers, and product leaders to mold enterprise-level GenAI platforms. Your responsibilities will include designing and scaling LLM-based systems such as chatbots, copilots, RAG, and multi-modal AI, architecting data pipelines, training/inference workflows, and integrating MLOps. You will be tasked with ensuring that systems are modular, secure, scalable, and cost-effective. Additionally, you will work on model orchestration, agentic AI, vector DBs, and CI/CD for AI. The ideal candidate should possess 12-15 years of experience in cloud-native and distributed systems, with 2-3 years focusing on GenAI/LLMs utilizing tools like LangChain, HuggingFace, and Kubeflow. Proficiency in cloud platforms such as AWS, GCP, or Azure (SageMaker, Vertex AI, Azure ML) is essential. Experience with RAG, semantic search, agent orchestration, and MLOps is highly valued. Strong architectural acumen, effective stakeholder communication skills, and preferred certifications in cloud technologies, AI open-source contributions, and knowledge of security and governance are all advantageous.,

You are an experienced Senior DevOps/MLOps Engineer who will be responsible for leading and managing a high-performing engineering team. Your main focus will be on overseeing the deployment and scaling of machine learning models and backend services using modern DevOps and MLOps practices. It is essential that you have proficiency in FastAPI, Docker, Kubernetes, and CI/CD. Your key responsibilities will include guiding and managing a team of DevOps/MLOps engineers, optimizing, containerizing, and deploying FastAPI applications at scale, managing infrastructure using tools like Terraform or Helm, handling multi-environment Kubernetes clusters (GKE, EKS, AKS, or on-prem), managing ML model lifecycle including versioning, deployment, monitoring, and rollback, designing and maintaining robust CI/CD pipelines for model and application deployment, setting up observability tools such as Prometheus, Grafana, ELK, ensuring secure infrastructure and data pipelines. Your required skills should include a deep understanding of building, scaling, and securing APIs with FastAPI, expert-level experience in Docker and Kubernetes for containerization and orchestration, familiarity with CI/CD tools like GitHub Actions, GitLab CI, Jenkins, ArgoCD, or similar, experience with cloud platforms such as AWS/GCP/Azure, strong scripting and automation skills with Python, and knowledge of ML Workflow Tools like MLflow, DVC, Kubeflow, or Seldon. Preferred qualifications for this role include experience in managing hybrid cloud/on-premise deployments, strong communication and mentoring skills, and an understanding of data pipelines, feature stores, and model drift monitoring. This is a full-time, permanent position that requires in-person work location.,

As a part of ZS, you will have the opportunity to work in a place driven by passion that aims to change lives. ZS is a management consulting and technology firm that is dedicated to enhancing life and its quality. The core strength of ZS lies in its people, who work collectively to develop transformative solutions for patients, caregivers, and consumers worldwide. By adopting a client-first approach, ZS employees bring impactful results to every engagement by partnering closely with clients to design custom solutions and technological products that drive value and yield positive outcomes in key areas of their business. Your role at ZS will require you to bring inquisitiveness for learning, innovative ideas, courage, and dedication to make a life-changing impact. At ZS, the individuals are highly valued, recognizing both the visible and invisible facets of their identities, personal experiences, and belief systems. These elements shape the uniqueness of each individual and contribute to the diverse tapestry within ZS. ZS acknowledges and celebrates personal interests, identities, and the thirst for knowledge as integral components of success within the organization. Learn more about the diversity, equity, and inclusion initiatives at ZS, along with the networks that support ZS employees in fostering community spaces, accessing necessary resources for growth, and amplifying the messages they are passionate about. As an Architecture & Engineering Specialist specializing in ML Engineering at ZS's India Capability & Expertise Center (CEC), you will be part of a team that constitutes over 60% of ZS employees across three offices in New Delhi, Pune, and Bengaluru. The CEC plays a pivotal role in collaborating with colleagues from North America, Europe, and East Asia to deliver practical solutions to clients that drive the company's operations. Upholding standards of analytical, operational, and technological excellence, the CEC leverages collective knowledge to enable ZS teams to achieve superior outcomes for clients. Joining ZS's Scaled AI practice within the Architecture & Engineering Expertise Center will immerse you in a dynamic ecosystem focused on generating continuous business value for clients through innovative machine learning, deep learning, and engineering capabilities. In this role, you will collaborate with data scientists to craft cutting-edge AI models, develop and utilize advanced ML platforms, establish and implement sophisticated ML pipelines, and oversee the entire ML lifecycle. **Responsibilities:** - Design and implement technical features using best practices for the relevant technology stack - Collaborate with client-facing teams to grasp the solution context, contribute to technical requirement gathering and analysis - Work alongside technical architects to validate design and implementation strategies - Write production-ready code that is easily testable, comprehensible to other developers, and addresses edge cases and errors - Ensure top-notch quality deliverables by adhering to architecture/design guidelines, coding best practices, and engaging in periodic design/code reviews - Develop unit tests and higher-level tests to handle expected edge cases, errors, and optimal scenarios - Utilize bug tracking, code review, version control, and other tools for organizing and delivering work - Participate in scrum calls, agile ceremonies, and effectively communicate progress, issues, and dependencies - Contribute consistently by researching and evaluating the latest technologies, conducting proofs-of-concept, and creating prototype solutions - Aid the project architect in designing modules/components of the overall project/product architecture - Break down large features into estimable tasks, lead estimation, and defend them with clients - Independently implement complex features with minimal guidance, such as service or application-wide changes - Systematically troubleshoot code issues/bugs using stack traces, logs, monitoring tools, and other resources - Conduct code/script reviews of senior engineers within the team - Mentor and cultivate technical talent within the team **Requirements:** - Minimum 5+ years of hands-on experience in deploying and productionizing ML models at scale - Proficiency in scaling GenAI or similar applications to accommodate high user traffic, large datasets, and reduce response time - Strong expertise in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex - Experience in crafting GenAI applications such as answering engines, extraction components, and content authoring - Expertise in designing, configuring, and utilizing ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other relevant platforms - Familiarity with Big data technologies including Hive, Spark, Hadoop, and queuing systems like Apache Kafka/Rabbit MQ/AWS Kinesis - Ability to quickly adapt to new technologies, innovate in solution creation, and independently conduct POCs on emerging technologies - Proficiency in at least one Programming language such as PySpark, Python, Java, Scala, etc., and solid foundations in Data Structures - Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, and ingestion patterns (batch, real-time) - Experience in designing and implementing solutions on distributed computing and cloud services platforms (e.g., AWS, Azure, GCP) - Hands-on experience in constructing CI/CD pipelines and awareness of application monitoring practices **Additional Skills:** - AWS/Azure Solutions Architect certification with a comprehensive understanding of the broader AWS/Azure stack - Knowledge of DevOps CI/CD, data security, and experience in designing on cloud platforms - Willingness to travel to global offices as required to collaborate with clients or internal project teams **Perks & Benefits:** ZS provides a holistic total rewards package encompassing health and well-being, financial planning, annual leave, personal growth, and professional development. The organization offers robust skills development programs, various career progression options, internal mobility paths, and a collaborative culture that empowers individuals to thrive both independently and as part of a global team. ZS is committed to fostering a flexible and connected work environment that enables employees to combine work from home and on-site presence at clients/ZS offices for the majority of the week. This approach allows for the seamless integration of the ZS culture and innovative practices through planned and spontaneous face-to-face interactions. **Travel:** Travel is an essential aspect of working at ZS, especially for client-facing roles. Business needs dictate the priority for travel, and while some projects may be local, all client-facing employees should be prepared to travel as required. Travel opportunities provide avenues to strengthen client relationships, gain diverse experiences, and enhance professional growth through exposure to different environments and cultures. **Application Process:** Candidates must either possess or be able to obtain work authorization for their intended country of employment. To be considered, applicants must submit an online application, including a complete set of transcripts (official or unofficial). *Note: NO AGENCY CALLS, PLEASE.* For more information, visit [ZS Website](www.zs.com).,

We are looking for a Systems Architect (AVP level) with extensive experience in designing and scaling Generative AI solutions for production. As a Systems Architect, you will play a crucial role in collaborating with data scientists, ML engineers, and product leaders to shape enterprise-grade GenAI platforms. Your responsibilities will include designing and scaling LLM-based systems such as chatbots, copilots, RAG, and multi-modal AI. You will also be responsible for architecting data pipelines, training/inference workflows, and MLOps integration. It is essential to ensure that the systems you design are modular, secure, scalable, and cost-effective. Additionally, you will work on model orchestration, agentic AI, vector DBs, and CI/CD for AI. The ideal candidate should have 12-15 years of experience in cloud-native and distributed systems, with at least 2-3 years of experience in GenAI/LLMs using tools like LangChain, HuggingFace, and Kubeflow. Proficiency in cloud platforms such as AWS, GCP, or Azure (SageMaker, Vertex AI, Azure ML) is required. Experience with technologies like RAG, semantic search, agent orchestration, and MLOps will be beneficial for this role. Strong architectural thinking and effective communication with stakeholders are essential skills. Preferred qualifications include cloud certifications, AI open-source contributions, and knowledge of security and governance principles. If you are passionate about designing cutting-edge Generative AI solutions and possess the necessary skills and experience, we encourage you to apply for this leadership role.,

7+ years of professional backend web development experience with Python. Experience of AI and RAG Experience with DevOps & IaC tools such as Terraform, Jenkins etc. Experience with MLOps platorms such as AWS Sagemaker, Kubeflow or MLflow.

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

You are a Java Developer with AI/ML experience, required to have at least 5+ years of industry experience in Java, Spring Boot, Spring Data, and a minimum of 2 years of AI/ML project or professional experience. You should possess a strong background in developing and consuming REST APIs and asynchronous messaging using technologies like Kafka or RabbitMQ. Your role involves integrating AI/ML models into Java services or making calls to external ML endpoints. You need to have a comprehensive understanding of the ML lifecycle encompassing training, validation, inference, monitoring, and retraining. Familiarity with tools such as TensorFlow, PyTorch, Scikit-Learn, or ONNX is essential. Previous experience in implementing domain-specific ML solutions like fraud detection, recommendation systems, or NLP chatbots is beneficial. Proficiency in working with various data formats including JSON, Parquet, Avro, and CSV is required. You should have a solid grasp of both SQL (PostgreSQL, MySQL) and NoSQL (Redis) database systems. Your responsibilities will include integrating machine learning models (both batch and real-time) into backend systems and APIs, optimizing and automating AI/ML workflows using MLOps best practices, and monitoring model performance, versioning, and rollbacks. Collaboration with cross-functional teams such as DevOps, SRE, and Product Engineering is necessary to ensure smooth deployment. Exposure to MLOps tools like MLflow, Kubeflow, or Seldon is desired. Experience with at least one cloud platform, preferably AWS, and knowledge of observability tools, metrics, events, logs, and traces (e.g., Prometheus, Grafana, Open Telemetry, Splunk, Data Dog, App Dynamics) are valuable skills in this role. Thank you. Aatmesh,

As an AI/ML Engineer, you will be a valuable member of our team, contributing to the development of intelligent systems that harness the power of machine learning and artificial intelligence. Your primary responsibilities will include designing, creating, and implementing machine learning models to address a variety of use cases, such as prediction, classification, NLP, and computer vision. You will collaborate closely with diverse teams to deliver innovative solutions that tackle real-world challenges effectively. Your key responsibilities will involve: - Designing and implementing machine learning models and algorithms for different applications. - Analyzing and preprocessing extensive datasets to establish resilient training pipelines. - Staying abreast of the latest advancements in AI/ML through research and integrating relevant techniques into projects. - Training, fine-tuning, and optimizing models to ensure high performance and scalability. - Deploying models into production environments using tools like Docker, Kubernetes, or cloud services (AWS, GCP, Azure). - Working alongside software engineers, data scientists, and product teams to seamlessly integrate AI/ML solutions into applications. - Monitoring model performance in production, continuously iterating for enhancements, and documenting design decisions, code, and models for transparency and reproducibility. Preferred qualifications for this role include: - Proficiency in NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). - Familiarity with deep learning architectures like CNNs, RNNs, GANs, or transformer models. - Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). - Previous contributions to open-source AI/ML projects or publications in relevant conferences/journals. If you are passionate about AI/ML technologies and eager to work on cutting-edge solutions that make a meaningful impact, we encourage you to apply for this exciting opportunity to join our dynamic team.,

As a GEN AI and Machine Learning Engineer, you will be responsible for leveraging your Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or a related field to develop and deploy machine learning and AI models. With a solid foundation in mathematics, statistics, and probability, you will utilize your strong programming skills in Python and proficiency in SQL/NoSQL databases to build analytical approaches based on business requirements. Your hands-on experience with Agentic AI frameworks will be crucial in building AI-driven features and solutions by collaborating with software engineers, business stakeholders, and domain experts. You will have the opportunity to work with Generative AI models and tools like OpenAI, Google Gemini, and Runway ML, in addition to AI/ML and deep learning frameworks such as TensorFlow, PyTorch, Scikit-learn, OpenCV, and Keras. In this role, you will preprocess and analyze large-scale datasets to extract meaningful insights, identify trends, and develop RESTful APIs using Flask or Django. Proficiency in cloud environments like AWS, Azure, or GCP will be essential as you deploy AI/ML applications and continuously monitor model performance for accuracy, scalability, and generalization. Additionally, your familiarity with ML operations tools such as MLFlow, Kubeflow, and CI/CD pipelines will be advantageous in evaluating and optimizing model performance. Experience with Docker, Kubernetes, and container orchestration, as well as frontend technologies like HTML, CSS, JavaScript/jQuery, Node.js, Angular, or React, will be beneficial for this role. Overall, as a GEN AI and Machine Learning Engineer, you will play a key role in designing, developing, and deploying AI/ML, NLP/NLU, and deep learning models and applications. Your ability to document development processes, results, and best practices will contribute to transparency and continuous learning within the organization.,

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Manager , Data Scientist We are seeking a tenured and highly skilled Data Scientist with deep expertise in Computer Vision and a strong foundation in AI/ML modeling. The ideal candidate will not only lead the development of intelligent vision systems but will also serve as a technical mentor, providing guidance to junior data scientists on model selection, optimization, and deployment strategies. Experience in domains such as energy, power generation, industrial equipment, or manufacturing will be considered a strong advantage, as the role involves solving real-world visual AI /ML problems in industrial environments. Key Responsibilities: Lead CV Projects: Design and deliver Computer Vision models across a range of use cases (e.g., anomaly detection, visual inspections, OCR, predictive maintenance). Model Development: Develop, evaluate, and optimize state-of-the-art AI/ML models (e.g., CNNs, Vision Transformers, YOLO, Faster R-CNN, etc.). Mentorship: Guide junior and mid-level data scientists on best practices in feature engineering, model selection, evaluation metrics, and problem-solving strategies. Domain Translation: Translate complex industrial problems into AI-driven CV solutions that can scale in production environments. Collaboration: Work closely with software engineers, MLOps , and business teams to ensure model integration and operational success. Code Quality & Experimentation: Drive code modularity, reproducibility, and experimentation through use of ML pipelines, version control, and testing. Innovation & Research: Stay current with latest CV and AI/ML advancements and apply them appropriately to business problems. Stakeholder Communication: Present insights, models, and outcomes in a clear and impactful way to both technical and non-technical stakeholders. Required Qualifications: Master&rsquos or PhD in Computer Science, Machine Learning, AI, Electrical Engineering, or a related field. Sound experience in building and deploying machine learning models, with a strong portfolio in Computer Vision. Deep expertise in ML frameworks and CV libraries such as PyTorch , TensorFlow, OpenCV, Detectron2, MMDetection , etc. Solid understanding of core AI/ML algorithms - classification, regression, segmentation, object detection, time-series, clustering, etc. Experience with MLOps tools (e.g., MLflow , DVC, Kubeflow) and cloud platforms (AWS/GCP/Azure). Strong communication , leadership, and team collaboration skills . Preferred Qualifications: Prior experience in domains such as energy, utilities, power generation, or industrial systems is highly preferred. Experience deploying CV models within real-time environments. Contributions to open-source CV projects or published research. Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.