1795 Mlflow Jobs - Page 4

Job Title: Data Engineer - Senior Location: Noida Employment Type: Permanent Experience Required: Minimum 5 years Primary Skills: Cloud - AWS (AWS Lambda, AWS EventBridge, AWS Fargate) --- Job Description We are seeking a highly skilled Senior Data Engineer to design, implement, and maintain scalable data pipelines that support machine learning model training and inference. Responsibilities: Build and maintain large-scale data pipelines ensuring scalability, reliability, and efficiency. Collaborate with data scientists to streamline the deployment and management of machine learning models. Design and optimize ETL (Extract, Transform, Load) processes and integrate data from multiple sources into structured storage systems. Automate ML workflows using MLOps tools and frameworks (e.g., Kubeflow, MLflow, TensorFlow Extended - TFX). Monitor model performance, data lineage, and system health in production environments. Work cross-functionally to improve data architecture and enable seamless ML model integration. Manage and optimize cloud platforms and data storage solutions (AWS, GCP, Azure). Ensure data security, integrity, and compliance with governance policies. Troubleshoot and optimize pipelines to improve reliability and performance. --- Required Skills Languages: Python, SQL, PySpark Cloud: AWS Services (Lambda, EventBridge, Fargate), Cloud Platforms (AWS, GCP, Azure) DevOps: Docker, Kubernetes, Containerization ETL Tools: AWS Glue, SQL Server (SSIS, SQL Packages) Nice to Have: Redshift, SAS dataset knowledge --- Mandatory Competencies DevOps/Configuration Management: Docker DevOps/Configuration Management: Cloud Platforms - AWS DevOps/Configuration Management: Containerization (Docker, Kubernetes) ETL: AWS Glue Database: SQL Server - SQL Packages

Job Description: 7–10 years of industry experience, with at least 5 years in machine learning roles. Advanced proficiency in Python and common ML libraries: TensorFlow, PyTorch, Scikit-learn. Experience with distributed training, model optimization (quantization, pruning), and inference at scale. Hands-on experience with cloud ML platforms: AWS (SageMaker), GCP (Vertex AI), or Azure ML. Familiarity with MLOps tooling: MLflow, TFX, Airflow, or Kubeflow; and data engineering frameworks like Spark, dbt, or Apache Beam. Strong grasp of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay). Excellent problem-solving, communication, and documentation skills.

Key Skills Required: 5+ years of experience in Software Engineering and MLOps Strong development experience on AWS, specifically AWS Sagemaker (mandatory) Experience with MLflow, GitLab, CDK (mandatory) Exposure to AWS Data Zone (preferred) Proficient in at least one general-purpose programming language: Python, R, Scala, Spark Hands-on experience with production-grade development, integration, and support Strong adherence to scalable, secure, and reliable application development best practices Candidate should have a strong analytical mindset and contribute to MLOps research initiatives

🚀 We're Hiring: Data Scientist (AI/ML | Industrial IoT | Time Series) 📍 Location: Hyderabad 🧠 Experience: 5+ Years Join our AI/ML initiative to predict industrial alarms from complex sensor data in refinery environments. You'll lead the development of predictive models using time series data, maintenance logs, and work in an Expert-in-the-Loop (EITL) setup with domain experts. 🔍 Key Responsibilities: Develop ML models for anomaly detection & alarm prediction from sensor/IoT time series data. Collaborate with domain experts to validate model outputs. Implement data preprocessing, feature engineering & scalable pipelines. Monitor model performance, drift, explainability (SHAP, confidence), and retraining. Contribute to production-grade MLOps workflows. ✅ What You Bring: 5+ yrs experience in Data Science/ML, especially with time series models (LSTM, ARIMA, Autoencoders). Proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch). Hands-on with IoT/sensor data in manufacturing/industrial domains. Experience with MLOps tools (MLflow, SageMaker, Kubeflow). Strong grasp of model interpretability, ETL (Pandas, PySpark, SQL), and cloud deployment. ✨ Bonus Points: Background in oil & gas, SCADA systems, maintenance logs, or industrial control systems. Experience with cloud platforms (AWS/GCP/Azure) and alarm classification standards.

🌟 We're Hiring: Artificial Intelligence (AI) Consultant! 🌟 We are seeking an experienced AI Consultant to drive innovative artificial intelligence solutions and guide organizations through their digital transformation journey. The ideal candidate will have deep expertise in AI technologies, machine learning algorithms, and strategic implementation to deliver impactful business solutions. 📍 Location: Chennai, India ⏰ Work Mode: Flexible office & remote 💼 Role: Artificial Intelligence (AI) Consultant What You'll Do Roles and Responsibilities AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction. Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks. LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB). Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines. Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives. Hands-on Prototyping: Rapidly prototype PoCs using Python and modern ML/LLM stacks to demonstrate feasibility and business impact. Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings Essential Skills Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact. Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains. Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models. LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration. Independent Contributor: Ability to own initiatives end-to-end, take decisions independently, and operate in fast-paced environments. Education Bachelor's or Master’s in Computer Science, AI, Engineering, or related field. Experience: Minimum 5 years of experience in consulting or technology roles, with at least 3 years focused on AI & ML solutions. Preferred Skills Cloud Platform Expertise: Strong familiarity with Microsoft Azure (preferred), AWS, or GCP — including compute instances, storage, managed services, and serverless/cloud- native deployment models. Programming Paradigms: Hands-on experience with both functional and object-oriented programming in AI system design. Hugging Face Ecosystem: Proficiency in using Hugging Face Transformers, Datasets, and Model Hub. Vector Store Experience: Hands-on experience with FAISS, Qdrant, Pinecone, ChromaDB. LangChain Expertise: Strong proficiency in LangChain for agentic task orchestration and RAG pipelines. MLOps & Deployment: CI/CD for ML pipelines, MLOps tools (MLflow, Azure ML), containerization (Docker/Kubernetes). Cloud & Service Architecture: Knowledge of microservices, scaling strategies, inter- service communication. Programming Languages: Proficiency in Python and C# for enterprise-grade AI solution development. Additional Skills Excellent customer interfacing and stakeholder engagement skills. Strong verbal and written communication in business and technical contexts. High attention to detail and structured problem-solving. Passion for AI ethics, safety, performance, and optimization in enterprise-grade systems.

About Position : We are seeking a seasoned Senior Data Architect with deep expertise in Databricks and Microsoft Fabric. This role involves leading the design and implementation of scalable data solutions for BFSI and HLS clients. Role: Senior Data Architect (Databricks & Microsoft Fabric) Location: All PSL Locations Experience: 10-18 Years Job Type: Full Time Employment What You'll Do: Architect and implement scalable, secure, and high-performance data solutions on the Databricks and Azure Fabric. Lead discovery workshops to understand business challenges, data requirements, and current technology ecosystems. Design end-to-end data pipelines, ensuring seamless integration with enterprise systems leveraging Databricks and Microsoft Fabric Optimize databricks and fabric workloads for performance and cost efficiency Provide solutions considering various architectural concerns e.g. Data Governance, Master Data Management, Meta-Data management, Data Quality Management, data security and privacy policies and procedures Optimize solutions for cost efficiency, performance, and reliability. Lead technical engagements, collaborating with client stakeholders and internal teams. Establish and enforce governance, security, and compliance standards within Databricks and Fabric Guide teams in implementing best practices on Databricks and Microsoft Azure. Keeping abreast with latest developments in the industry; evaluating and recommending new and emerging data architectures/patterns, technologies, and standards Act as a subject matter expert (SME) for Databricks and Azure Fabric within the organization and for clients. Delivering and directing pre-sales engagements to prove functional capabilities (POC’s or POV’s) Develop and deliver workshops, webinars, and technical presentations on Databricks and Fabric capabilities. Create white papers, case studies and reusable artifacts to showcase our company’s Databricks value proposition. Build strong relationships with Databricks partnership teams including their product managers and solution architects, contributing to co-marketing and joint go-to-market strategies. Business Development Support: Collaborate with sales and pre-sales teams to provide technical guidance during RFP responses and solutioning. Identify upsell and cross-sell opportunities within existing accounts by showcasing Databricks’s & BI potential for extended use cases. Expertise You'll Bring: Minimum of 10+ years of experience in data architecture, engineering, or analytics roles, with at least 5 years of hands-on experience with Databricks and 1 year of Azure Fabric Proven track record of designing and implementing large-scale data solutions across industries. Experience working in consulting or client-facing roles, particularly with enterprise customers. Deep understanding of modern data architecture principles, including cloud platforms (AWS, Azure, GCP). Deep expertise in modern data architectures, lakehouse principles, and AI-driven analytics. Strong hands-on experience with Databricks core components, including Delta Lake, Apache Spark, MLflow, Unity Catalog, and Databricks Workflows. Understanding of cloud-native services for data ingestion, transformation, and orchestration (e.g., AWS Glue, Azure Data Factory, GCP Dataflow). Exceptional communication and presentation skills, capable of explaining technical concepts to non-technical stakeholders. Strong interpersonal skills to foster collaboration with diverse teams. A self-starter with a growth mindset and the ability to adapt in a fast-paced environment. Databricks Advanced Certification Databricks Certified Data Engineer Professional Certifications in cloud platforms such as: AWS Certified Data Analytics: Specialty Microsoft Certified: Azure Data Engineer Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents Inclusive Environment: Persistent Ltd. is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds. We offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities. If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry’s best Let’s unleash your full potential at Persistent “Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”

🌟 We're Hiring: Artificial Intelligence (AI) Consultant! 🌟 We are seeking an experienced AI Consultant to drive innovative artificial intelligence solutions and guide organizations through their digital transformation journey. The ideal candidate will have deep expertise in AI technologies, machine learning algorithms, and strategic implementation to deliver impactful business solutions. 📍 Location: Chennai, India ⏰ Work Mode: Flexible office & remote 💼 Role: Artificial Intelligence (AI) Consultant What You'll Do Roles and Responsibilities AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction. Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks. LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB). Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines. Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives. Hands-on Prototyping: Rapidly prototype PoCs using Python and modern ML/LLM stacks to demonstrate feasibility and business impact. Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings Essential Skills Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact. Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains. Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models. LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration. Independent Contributor: Ability to own initiatives end-to-end, take decisions independently, and operate in fast-paced environments. Education Bachelor's or Master’s in Computer Science, AI, Engineering, or related field. Experience: Minimum 5 years of experience in consulting or technology roles, with at least 3 years focused on AI & ML solutions. Preferred Skills Cloud Platform Expertise: Strong familiarity with Microsoft Azure (preferred), AWS, or GCP — including compute instances, storage, managed services, and serverless/cloud- native deployment models. Programming Paradigms: Hands-on experience with both functional and object-oriented programming in AI system design. Hugging Face Ecosystem: Proficiency in using Hugging Face Transformers, Datasets, and Model Hub. Vector Store Experience: Hands-on experience with FAISS, Qdrant, Pinecone, ChromaDB. LangChain Expertise: Strong proficiency in LangChain for agentic task orchestration and RAG pipelines. MLOps & Deployment: CI/CD for ML pipelines, MLOps tools (MLflow, Azure ML), containerization (Docker/Kubernetes). Cloud & Service Architecture: Knowledge of microservices, scaling strategies, inter- service communication. Programming Languages: Proficiency in Python and C# for enterprise-grade AI solution development. Additional Skills Excellent customer interfacing and stakeholder engagement skills. Strong verbal and written communication in business and technical contexts. High attention to detail and structured problem-solving. Passion for AI ethics, safety, performance, and optimization in enterprise-grade systems.

Job Summary Job Title: AI/ML Engineer Location: TechM Blr ECITY Years of Experience: 10+ Years Job Summary Chevron invites applications for the role of AI/ML Engineer within our Enterprise AI team in India. This position is integral to designing and developing AI/ML models that significantly accelerate the delivery of business value. We are looking for a Machine Learning Engineer with the ability to bring their expertise, innovative attitude, and excitement for solving complex problems with modern technologies and approaches. We seek individuals with a passion for exploring, innovating, and delivering innovative Data Science solutions that provide immense value to our business. Responsibilities Design and develop AI/ML models to enhance business processes and deliver actionable insights. Implement machine learning frameworks and libraries, ensuring robust model performance and scalability. Collaborate with cross functional teams to integrate AI solutions into existing workflows. Manage the lifecycle of machine learning models, including training, validation, deployment, and monitoring. Develop and maintain custom APIs for machine learning models to facilitate training and inference. Utilize Azure services to build and deploy machine learning pipelines effectively. Engage with technical experts to identify opportunities for applying machine learning and analytics. Communicate findings and insights clearly to stakeholders at all levels. Mandatory Skills Minimum 5 years of experience in Object Oriented Programming in Python. Proven experience with Azure IaaS services, particularly in building machine learning pipelines using Azure Machine Learning and/or Fabric. Strong understanding of software engineering principles, including source control, architecture, and testing methodologies. Experience with containers and container management (Docker, Kubernetes). Proficient in orchestrating large scale ML/DL jobs and leveraging Modern Data Platform tooling. Experience in designing custom APIs for machine learning models. Knowledge of mathematics (linear algebra, probability, Statistics) and algorithms. Ability to communicate effectively in both oral and written forms. Preferred Skills Experience implementing machine learning frameworks such as MLflow. Familiarity with Data Engineering and transformation tools like Azure Databricks, Spark, and Azure ADF. History of working with large scale model optimization and Neural Networks Hyper Parameter Tuning. Experience with unstructured data using Azure Cognitive Services and/or Computer Vision. Understanding of enterprise SaaS complexities, including security, scalability, and production support. Qualifications Bachelor's or Master's degree in Computer Science, Data Science, or a related field. 7 10 years of relevant experience in AI/ML engineering. Strong problem solving skills and a methodical approach to software design and development.

Role: Machine Learning Engineer - MLOps Job Overview As a Senior Software Development Engineer, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Team Overview Your team’s goal will be to reduce friction and time-to-business-value for teams building Artificial Intelligence (AI) solutions at PitchBook. You will be essential in helping to build exceptional AI solutions relied upon and used by thousands of PitchBook customers every day. You will work with PitchBook professionals around the world with the collective goal of delighting our customers and growing our business. While demonstrating a growth mindset, you will be expected to continuously develop your expertise in a way that enhances PitchBook’s AI capabilities in a scalable and repeatable manner. You will be able to solve various common challenges faced in the MLDLC while providing technical guidance to less experienced peers. Outline Of Duties And Responsibilities Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment Design and deliver on projects end-to-end with little to no guidance Provide support to teams building and deploying AI applications by addressing common painpoints in the MLDLC Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities Support the vision and values of the company through role modeling and encouraging desired behaviors. Participate in various cross-functional company initiatives and projects as requested. Contribute to strategic planning in a way that ensures the team is building exceptional products that bring real business value. Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance. Experience, Skills And Qualifications Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or commensurate experience) +2 years of experience in hands-on development of Machine Learning algorithms +2 years of experience in hands-on deployment of Machine Learning services +2 years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance +2 years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP) Experience with at least 80%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, KubeFlow Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement Experience in cloud-native delivery, with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions. Proficiency in GitOps and creation/management of CI/CD pipelines Demonstrated experience building and using SQL/NoSQL databases Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools. Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context. Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions. Ability to be a team player who can also work independently Experience working across multiple development teams is a plus Working Conditions The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events. Morningstar India is an equal opportunity employer Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues. I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

Description / Position Overview This is a key position for our client to help create data-driven technology solutions that will position us as the industry leader in healthcare, financial, and clinical administration. This hands-on Lead Data Scientist role will focus on building and implementing machine learning models and predictive analytics solutions that will drive the new wave of AI-powered innovation in healthcare. You will be the lead data science technologist responsible for developing and implementing a multitude of ML/AI products from concept to production, helping us gain a competitive advantage in the market. Alongside our Director of Data Science, you will work at the intersection of healthcare, finance, and cutting-edge data science to solve some of the industry's most complex challenges. This is a greenfield opportunity within VHT’s Product Transformation division, where you'll build groundbreaking machine learning capabilities from the ground up. You'll have the chance to shape the future of VHT’s data science & analytics foundation while working with cutting-edge tools and methodologies in a collaborative, innovation-driven environment. Key Responsibilities As the Lead Data Scientist, your role will require you to work closely with subject matter experts in clinical and financial administration across practices, health systems, hospitals, and payors. Your machine learning projects will span the entire healthcare revenue cycle - from clinical encounters through financial transaction completion, extending into back-office operations and payer interactions. You will lead the development of predictive machine learning models for Revenue Cycle Management analytics, along the lines of: • Payer Propensity Modeling - predicting payer behavior and reimbursement likelihood • Claim Denials Prediction - identifying high-risk claims before submission • Payment Amount Prediction - forecasting expected reimbursement amounts • Cash Flow Forecasting - predicting revenue timing and patterns • Patient-Related Models - enhancing patient financial experience and outcomes • Claim Processing Time Prediction - optimizing workflow and resource allocation Additionally, we will work on emerging areas and integration opportunities—for example, denial prediction + appeal success probability or prior authorization prediction + approval likelihood models. You will reimagine how providers, patients, and payors interact within the healthcare ecosystem through intelligent automation and predictive insights, ensuring that providers can focus on delivering the highest quality patient care. VHT Technical Environment • Cloud Platform : AWS (SageMaker, S3, Redshift, EC2) • Development Tools : Jupyter Notebooks, Git, Docker • Programming : Python, SQL, R (optional) • ML/AI Stack : Scikit-learn, TensorFlow/PyTorch, MLflow, Airflow • Data Processing : Spark, Pandas, NumPy • Visualization : Matplotlib, Seaborn, Plotly, Tableau Required Qualifications • Advanced degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field • 5+ years of hands-on data science experience with a proven track record of deploying ML models to production • Expert-level proficiency in SQL and Python , with extensive experience using standard Python machine learning libraries (scikit-learn, pandas, numpy, matplotlib, seaborn, etc.) • Cloud platform experience, preferably AWS, with hands-on knowledge of SageMaker, S3, Redshift, and Jupyter Notebook workbenches (other cloud environments acceptable) • Strong statistical modeling and machine learning expertise across supervised and unsupervised learning techniques • Experience with model deployment, monitoring, and MLOps practices • Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders Preferred Qualifications • US Healthcare industry experience , particularly in Health Insurance and/or Medical Revenue Cycle Management • Experience with healthcare data standards (HL7, FHIR, X12 EDI) • Knowledge of healthcare regulations (HIPAA, compliance requirements) • Experience with deep learning frameworks (TensorFlow, PyTorch) • Familiarity with real-time streaming data processing • Previous leadership or mentoring experience

🚀 We’re Hiring: ML Ops / Data Engineer (Minimum 5 Years Experience) 🚀 Are you a data engineering professional with at least 5 years of experience in building scalable data pipelines and deploying machine learning models? We’re looking for a talented ML Ops / Data Engineer to join our team in Noida! 🔍 What You’ll 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 using AWS Glue, PySpark, and SQL Automate ML workflows using tools like Kubeflow, MLflow, or TFX 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 experience in data engineering or ML Ops Proficiency in AWS Services (Lambda, EventBridge, Fargate) Strong knowledge of SQL, Docker, and Kubernetes Experience with AWS Glue, PySpark, and containerized environments 📍 Location: Noida 💼 Employment Type: Permanent 🔑 Primary Skill: AWS Cloud, ML Ops, Data Engineering If you're ready to take your career to the next level and work on cutting-edge ML infrastructure, we’d love to connect! #Hiring #MLOps #DataEngineering #AWSJobs #ETL #MachineLearning #NoidaJobs #TechCareers #DataPipelines #5YearsExperience

Transforming the Future of Enterprise Planning At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions—even billions—in value leakage, we help businesses plan smarter and faster. This not only enhances operational efficiency but also reduces waste, leading to better outcomes for both businesses and the planet. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains. Job Title: DevOps Engineer - AI, R&D Location: Bengaluru, Karnataka, India (hybrid) About o9 Solutions: o9 Solutions is a leading enterprise AI software platform provider for transforming planning and decision-making capabilities. We are building the next generation of AI-powered solutions to help businesses optimize their operations and drive innovation. Our Next-Gen AI R&D team is at the forefront of this mission, pushing the boundaries of what's possible with artificial intelligence. About the Role... We are looking for a highly skilled and motivated DevOps Engineer to join our Next-Gen AI R&D team. In this role, you will be instrumental in developing and implementing MLOps strategies for Generative AI models, designing and managing CI/CD pipelines for ML workflows, and ensuring the robustness, scalability, and reliability of our AI solutions in production environments. What you will do in this role: Develop and implement MLOps strategies tailored for Generative AI models to ensure robustness, scalability, and reliability. Design and manage CI/CD pipelines specialized for ML workflows, including the deployment of generative models such as GANs, VAEs, and Transformers. Monitor and optimize the performance of AI models in production, employing tools and techniques for continuous validation, retraining, and A/B testing. Collaborate with data scientists and ML researchers to understand model requirements and translate them into scalable operational frameworks. Implement best practices for version control, containerization, infrastructure automation, and orchestration using industry-standard tools (e.g., Docker, Kubernetes). Ensure compliance with data privacy regulations and company policies during model deployment and operation. Troubleshoot and resolve issues related to ML model serving, data anomalies, and infrastructure performance. Stay up-to-date with the latest developments in MLOps and Generative AI, bringing innovative solutions to enhance our AI capabilities. What you'll have.. Must Have: Minimum 3 years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing proofs of concept and prototypes. Strong background in software development, with experience in building and maintaining scalable, distributed systems. Strong programming skills in languages like Python and familiarity in ML frameworks and libraries (e.g., TensorFlow, PyTorch). Knowledge of containerization and orchestration tools like Docker and Kubernetes. Proficiency with MLOps tools such as MLflow, Kubeflow, Airflow, or similar for managing machine learning workflows and lifecycle. Practical understanding of generative AI frameworks (e.g., HuggingFace Transformers, OpenAI GPT, DALL-E). Expertise in containerization technologies like Docker and orchestration tools such as Kubernetes for scalable model deployment. Expertise in MLOps and LLMOps practices, including CI/CD for ML models. Nice to Have: Familiarity with cloud platforms (AWS, GCP, Azure) and their ML/AI service offerings. Experience with continuous integration and delivery tools such as Jenkins, GitLab CI/CD, or CircleCI. Experience with infrastructure as code tools like Terraform or CloudFormation. Experience with advanced GenAI applications such as natural language generation, image synthesis, and creative AI. Familiarity with experiment tracking and model registry tools. Knowledge of high-performance computing and parallel processing techniques. Contributions to open-source MLOps or GenAI projects. What we’ll do for you: Flat organization: With a very strong entrepreneurial culture (and no corporate politics). Great people and unlimited fun at work. Possibility to really make a difference in a scale-up environment. Support network: Work with a team you can learn from every day. Diversity: We pride ourselves on our international working environment. AI is firmly on every CEO's agenda, o9 @ Davos & Reflections: https://o9solutions.com/articles/why-ai-is-topping-the-ceo-agenda/ Work-Life Balance: https://youtu.be/IHSZeUPATBA?feature=shared Feel part of A team: https://youtu.be/QbjtgaCyhes?feature=shared How the process works... Respond with your interest to us. We’ll contact you either via video call or phone call - whatever you prefer, with the further schedule status. During the interview phase, you will meet with the technical panel for 60 minutes. We will contact you after the interview to let you know if we’d like to progress your application. There will be 2-3 rounds of technical discussion followed by a Managerial round. We will let you know if you’re the successful candidate. Good luck! Why Join o9 Solutions? At o9, you'll be at the forefront of AI innovation, working with a dynamic team that's shaping the future of enterprise solutions. We offer a stimulating and rewarding environment where your contributions directly impact cutting-edge projects. You'll gain invaluable experience with the latest AI technologies and significantly grow your skills. Join us and be a key player in building the next generation of intelligent solutions that truly transform businesses! More about us… At o9, transparency and open communication are at the core of our culture. Collaboration thrives across all levels—hierarchy, distance, or function never limit innovation or teamwork. Beyond work, we encourage volunteering opportunities, social impact initiatives, and diverse cultural celebrations. With a $3.7 billion valuation and a global presence across Dallas, Amsterdam, Barcelona, Madrid, London, Paris, Tokyo, Seoul, and Munich, o9 is among the fastest-growing technology companies in the world. Through our aim10x vision, we are committed to AI-powered management, driving 10x improvements in enterprise decision-making. Our Enterprise Knowledge Graph enables businesses to anticipate risks, adapt to market shifts, and gain real-time visibility. By automating millions of decisions and reducing manual interventions by up to 90%, we empower enterprises to drive profitable growth, reduce inefficiencies, and create lasting value. o9 is an equal-opportunity employer that values diversity and inclusion. We welcome applicants from all backgrounds, ensuring a fair and unbiased hiring process. Join us as we continue our growth journey!

About the Role We are seeking a highly experienced and strategic AI/ML Architect to lead the design, development, and deployment of scalable artificial intelligence and machine learning solutions. As a core member of our technical leadership team, you will play a pivotal role in building intelligent systems that drive innovation and transform digital healthcare delivery across our AI Driven Telemedicine platform. Key Responsibilities Architect AI/ML systems that support key business goals, from real-time diagnosis and predictive analytics to natural language conversations and recommendation engines. Design and oversee machine learning pipelines, model training, validation, deployment, and performance monitoring. Guide selection of ML frameworks (e.g., TensorFlow, PyTorch) and ensure proper MLOps practices (CI/CD, model versioning, reproducibility, drift detection). Collaborate with cross-functional teams (data engineers, product managers, UI/UX, backend developers) to integrate AI into real-time applications and APIs. Build and maintain scalable AI infrastructure, including data ingestion, storage, and processing layers in cloud environments (AWS, GCP, or Azure). Lead research and experimentation on generative AI, NLP, computer vision, and deep learning techniques relevant to healthcare use cases. Define data strategies, governance, and model explainability/ethics frameworks to ensure compliance with regulatory standards like HIPAA. Mentor and lead a growing team of ML engineers and data scientists. Qualifications Must-Have: Bachelor's or Master’s degree in Computer Science, AI, Data Science, or related field (PhD preferred). 7+ years of experience in AI/ML development, with at least 2 years in a lead or architect role. Proven experience designing and deploying production-grade ML systems at scale. Strong grasp of ML algorithms, deep learning, NLP, computer vision, and generative AI. Expertise in Python, ML libraries (TensorFlow, PyTorch, Scikit-learn), and ML Ops tools (MLflow, Kubeflow, SageMaker, etc.). Familiarity with data engineering pipelines (Airflow, Spark, Kafka) and cloud platforms. Strong communication and collaboration skills. Preferred: Experience with healthcare data standards (FHIR, HL7) and medical ontologies (SNOMED CT, ICD). Familiarity with AI ethics, fairness, and interpretability frameworks. Startup or early-stage product development experience.

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

Job Title: Senior Python Developer AI/ML Document Automation Location: Hyderabad Work Mode: Hybrid Experience: 5+ Years Job Summary: We are looking for a highly skilled Senior Python Developer with deep expertise in AI/ML and document automation . The ideal candidate will lead the design and development of intelligent systems for extracting and processing structured and unstructured data from documents such as invoices, receipts, contracts, and PDFs. This role involves both hands-on coding and architectural contributions to scalable automation platforms. Roles and Responsibilities: Design and develop modular Python applications for document parsing and intelligent automation. Build and optimize ML/NLP pipelines for tasks like Named Entity Recognition (NER), classification, and layout-aware data extraction. Integrate rule-based and AI-driven techniques (e.g., regex, spaCy, PyMuPDF, Tesseract) to handle diverse document formats. Develop and deploy models via REST APIs using FastAPI or Flask, and containerize with Docker. Collaborate with cross-functional teams to define automation goals and data strategies. Conduct code reviews, mentor junior developers, and uphold best coding practices. Monitor model performance and implement feedback mechanisms for continuous improvement. Maintain thorough documentation of workflows, metrics, and architectural decisions. Mandatory Skills: Expert in Python (OOP, asynchronous programming, modular design). Strong foundation in machine learning algorithms and natural language processing techniques. Hands-on experience with Scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers. Proficient in developing REST APIs using FastAPI or Flask. Experience in PDF/text extraction using PyMuPDF, Tesseract, or similar tools. Skilled in regex-based extraction and rule-based NER. Familiar with Git, Docker, and any major cloud platform (AWS, GCP, or Azure). Exposure to MLOps tools such as MLflow, Airflow, or LangChain. 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

Job Title: AI Research Engineer Intern (Fresher) Reporting to: Lead – Research & Innovation Lab Location: remote/ Hybrid (Chennai, India) Engagement: 6-month, full-time paid internship with pre-placement-offer track 1. Why this role exists Stratsyn AI Technology Services is turbo-charging Stratsyn’s cloud-native Enterprise Intelligence & Management Suite —a modular SaaS ecosystem that fuses advanced AI, low-code automation, multimodal search, and next-generation “Virtual workforce” agents. The platform unifies strategic planning, document intelligence, workflow orchestration, and real-time analytics, empowering C-suite leaders to simulate scenarios, orchestrate execution, and convert insight into action with unmatched speed and scalability. To keep pushing that frontier, we need sharp, curious minds who can translate cutting-edge research into production-grade capabilities for this suite. This internship is our talent-funnel into future Research Engineer and Product Scientist roles. 2. What you’ll do (core responsibilities) % FocusKey Responsibility 30 %Rapid Prototyping & Experimentation – implement state-of-the-art papers (LLMs, graph learning, causal inference, agents), design ablation studies, benchmark against baselines, and iterate fast. 25 %Data Engineering for Research – build reproducible datasets, craft synthetic data when needed, automate ETL pipelines, and enforce experiment tracking (MLflow / Weights & Biases). 20 %Model Evaluation & Explainability – create evaluation harnesses (BLEU, ROUGE, MAPE, custom KPIs), visualize error landscapes, and generate executive-ready insights. 15 %Collaboration & Documentation – author tech memos, well-annotated notebooks, and contribute to internal knowledge bases; present findings in weekly research stand-ups. 10 %Innovation Scouting – scan arXiv, ACL, NeurIPS, ICML, and startup ecosystems; summarize high-impact research and propose areas for IP creation within the Suite. 3. What you will learn / outcomes to achieve Master the end-to-end research workflow: literature review → hypothesis → prototype → validation → deployment shadow. Deliver one peer-review-quality technical report and two production-grade proof-of-concepts for the Suite. Achieve a measurable impact (e.g., 8-10 % forecasting-accuracy lift or 30 % latency reduction) on a live micro-service. 4. Minimum qualifications (freshers welcome) B.E./B.Tech/M.Sc./M.Tech in CS, Data Science, Statistics, EE, or related (2024-2026 pass-out). Fluency in Python and at least one deep-learning framework (PyTorch preferred). Solid grasp of linear algebra, probability, optimization, and algorithms. Hands-on academic or personal projects in NLP, CV, time-series, or RL (GitHub links highly valued). 5. Preferred extras Publications or Kaggle/ML-competition record. Experience with distributed training (GPU clusters, Ray, Lightning) and experiment-tracking tools. Familiarity with MLOps (Docker, CI/CD, Kubernetes) or data-centric AI. Domain knowledge in supply-chain, fintech, climate, or marketing analytics. 6. Key attributes & soft skills First-principles thinker – questions assumptions, proposes novel solutions. Bias for action – prototypes in hours, not weeks; embraces agile experimentation. Storytelling ability – explains complex models in clear, executive-friendly language. Ownership mentality – treats the prototype as a product, not just a demo. 7. Tech stack you’ll touch Python | PyTorch | Hugging Face | TensorRT | LangChain | Neo4j/GraphDB | PostgreSQL | Airflow | MLflow | Weights & Biases | Docker | GitHub Actions | JAX (exploratory) 8. Internship logistics & perks Competitive monthly stipend + performance bonus. High-end workstation + GPU credits on our private cloud. Dedicated mentor and 30-60-90-day learning plan. Access to premium research portals and paid conference passes. Culture of radical candor, weekly brown-bag tech talks, and hack days. Fast-track to full-time AI Research Engineer upon successful completion. 9. Application process Apply via email: Send résumé, brief statement of purpose, and GitHub/portfolio links to HR@stratsyn.ai . Online coding assessment: algorithmic + ML fundamentals. Technical interview (2 rounds): deep dive into projects, math, and research reasoning. Culture-fit discussion: with Research Lead & CPO. Offer & onboarding – target turnaround < 3 weeks.

We are looking for MLops Engineer@ Gurgaon Location Job Responsibilities: Design and implement CI/CD pipelines for machine learning workflows. Develop and maintain production-grade ML pipelines using tools like MLflow, Kubeflow, or Airflow. Automate model training, testing, deployment, and monitoring processes. Collaborate with Data Scientists to operationalize ML models, ensuring scalability and performance. Monitor deployed models for drift, degradation, and bias, and trigger retraining as needed. Maintain and improve infrastructure for model versioning, artifact tracking, and reproducibility. Integrate ML solutions with microservices/APIs using FastAPI or Flask. Work on containerized environments using Docker and Kubernetes. Implement logging, monitoring, and alerting for ML systems (e.g., Prometheus, Grafana). Champion best practices in code quality, testing, and documentation. Required Skills: 7+ years of experience in Python development and ML/AI-related engineering roles. Strong experience in ML Ops tools like MLflow, Kubeflow, Airflow, or similar. Deep understanding of Docker, Kubernetes, and container orchestration for ML workflows. Hands-on experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform/CDK). Familiarity with model deployment and serving frameworks (e.g., Seldon, TorchServe, TensorFlow Serving). Good understanding of DevOps practices and CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI). Experience with data versioning tools (e.g., DVC) and model lifecycle management. Exposure to monitoring tools for ML and infrastructure healt Experience:7-12 Yrs Job Location :Gurgaon Interested candidates can share your CV to mangani.paramanandhan@bounteous.com, i will call you shortly. Please share your CV.

We are seeking a skilled and passionate AI/ML Engineer to join our team and help us develop intelligent systems that leverage machine learning and artificial intelligence. You will design, develop, and deploy machine learning models, work closely with cross-functional teams, and contribute to cutting-edge solutions that solve real-world problems. Responsibilities Design and implement machine learning models and algorithms for various use cases (e. g., prediction, classification, NLP, computer vision). Analyze and preprocess large datasets to build robust training pipelines. Research to stay up-to-date with the latest AI/ML advancements and integrate relevant techniques into projects. Train, fine-tune, and optimize models for performance and scalability. Deploy models to production using tools such as Docker, Kubernetes, or cloud services (AWS, GCP, Azure). Collaborate with software engineers, data scientists, and product teams to integrate AI/ML solutions into applications. Monitor model performance in production and continuously iterate for improvements. Document design choices, code, and models for transparency and reproducibility. Requirements Experience with NLP libraries (e. g., Hugging Face Transformers, spaCy) or computer vision tools (e. g., OpenCV). Preferred experience in Real Image Processing, and RAG-oriented. Background in deep learning architectures such as CNNs, RNNs, GANs, or transformer models. Knowledge of MLOps practices and tools (e. g., MLflow, Kubeflow, SageMaker). Contributions to open-source AI/ML projects or publications in relevant conferences/journals. This job was posted by Tista Saha from SentientGeeks.

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description As a Staff Machine Learning Engineer , you will drive AI programs, lead engagements, and independently develop innovative solutions that enhance decision-making, automate workflows, and create growth. You will own the end-to-end development of AI-powered applications, from solution design to deployment, leveraging pre-trained machine learning and generative AI models. You will work closely with cross-functional teams, proactively identifying opportunities to integrate AI capabilities into Experian's products and services while optimizing performance and scalability. Qualifications Experinece working in cloud environment with one of Databricks, Azure or AWS 8+ years experience building data-drive products and solutions Experience leading AI engagements Strong experience with AI APIs (OpenAI, Hugging Face, Google Vertex AI, AWS Bedrock) and fine-tuning models for production use. Deep understanding of machine learning, natural language processing (NLP), and generative AI evaluation techniques.Key Responsibilities Assist in Developing and Deploying Machine Learning Models: Support the development and deployment of machine learning models, including data preprocessing and performance evaluation in Python using sklearn, numpy and other standard libraries. Build and Maintain ML Pipelines: Help build and maintain scalable ML pipelines, and assist in automating model training workflows in Python using MLFlow, Databricks, Sagemaker or equivalent. Collaborate with Cross-Functional Teams: Work with product and data teams to align ML solutions with business needs and objectives. Write Clean and Documented Code: Write clean, well-documented code, following best practices for testing and version control. Use Sphinx and other auto documentation solutions to automate document generation. Support Model Monitoring and Debugging: Assist in monitoring and debugging models to improve their reliability and performance. Participate in Technical Discussions and Knowledge Sharing: Engage in technical discussions, code reviews, and knowledge-sharing sessions to learn and grow within the team. Day-to-Day ActivitiesOn a daily basis, you will work closely with senior ML engineers and data scientists to support various stages of the machine learning lifecycle. Your day-to-day activities will include: Data Preprocessing: Cleaning and preparing data for model training, ensuring data quality and consistency. Model Training: Assisting in the training of machine learning models, experimenting with different algorithms and hyperparameters. Performance Evaluation: Evaluating model performance using appropriate metrics and techniques, and identifying areas for improvement. Pipeline Maintenance: Building and maintaining ML pipelines, ensuring they are scalable and efficient. Code Development: Writing and maintaining clean, well-documented code, following best practices for testing and version control. Model Monitoring: Monitoring deployed models to ensure they are performing as expected, and assisting in debugging any issues that arise. Collaboration: Participating in team meetings, sprint planning, and daily stand-ups to stay aligned with project goals and timelines. Additional Information Our uniqueness is that we truly celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what truly matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's strong people first approach is award winning; Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few. Check out Experian Life on social or our Careers Site to understand why. Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, color, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. Experian Careers - Creating a better tomorrow together Benefits Experian care for employee's work life balance, health, safety and wellbeing. In support of this endeavor, we offer best-in-class family well-being benefits, enhanced medical benefits and paid time off. Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here

#Connections #Hiring #SeniorDataScientist #Hyderabad #Experience Hi Connections, We are hiring senior Data Scientist for our client. Role: Sr. Data Scientist (Predictive Analytics Focus & Data bricks) Experience: 5 Years Location: Hyderabad Responsibilities: Design and deploy predictive models (e.g., forecasting, churn analysis, fraud detection) using Python/SQL, Spark MLlib, and Databricks ML. Build end-to-end ML pipelines (data ingestion → feature engineering → model training → deployment) on Databricks Lakehouse. Optimize model performance via hyperparameter tuning, AutoML, and MLflow tracking. Collaborate with engineering teams to operationalize models (batch/real-time) using Databricks Jobs or REST APIs. Implement Delta Lake for scalable, ACID-compliant data workflows. Enable CI/CD for ML pipelines using Databricks Repos and GitHub Actions. Troubleshoot issues in Spark Jobs and Databricks Environment. Requirements: Experience should have 3 to 5 years in predictive analytics, with expertise in regression, classification, time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark. Familiarity with MLflow, Feature Store, and Unity Catalog for governance. Industry experience in Life Insurance or P&C. Good to have certification on Databricks Certified ML Practitioner. Technical Skills: Python, PySpark, MLflow, Databricks AutoML. Predictive Modelling (Classification, Clustering, Regression, timeseries and NLP). Cloud platform (Azure/AWS), Delta Lake, Unity Catalog. Interested guys, kindly share your updated profile to pavani@sandvcapitals.com or reach us on 7995292089. Thank you. Job Type: Full-time Pay: ₹1,500,000.00 - ₹1,800,000.00 per year Experience: Data Scientist: 4 years (Required) Work Location: In person

About Adsparkx: Adsparkx is a leading Global Performance Marketing Agency headquartered in India. We have been empowering brands since 2014 helping them acquire high quality and engaging users globally via data-driven decisions. We are innovators, hustlers and ad-tech moguls/experts who function with the belief of catalyzing a disruptive change in the industry by providing empowered and customized digital experiences to consumers/brands. Adsparkx unlocks the full potential of your business with its diligent workforce, catering to worldwide clients at their time zones. We operate globally and have offices in Gurgaon, Chandigarh, Singapore and US. We value partnerships and have maintained sustainable relationships with reputed brands, shaping their success stories through services like Affiliate Marketing, Branding, E-commerce, Lead Generation, and Programmatic Media Buying. We have helped navigate over 200 brands to success. Our clientele includes names like Assurance IQ, Inc, Booking.com, Groupon, etc. If you wish to change the game of your brand, visit us here- https://adsparkx.com/ Job Title: Ai Engineer Location: Gurugram, Haryana Employment Type: Full-Time Experience Required: 4-6 Years Objective of the Role: We are seeking a highly skilled Ai Enginee r who will be responsible for building, testing, and maintaining robust, scalable, and secure web applications. The ideal candidate will have strong expertise in Python and Django , with additional exposure to machine learning , generative AI frameworks , and modern deep learning architectures . This role involves optimizing performance, ensuring security, working with APIs, and collaborating closely with cross-functional teams to deliver high-quality backend solutions. Key Responsibilities: 3-6 years of hands-on experience in Python. Design, develop, and maintain backend services and RESTful APIs using Django or Django REST Framework. Work with third-party APIs and external services to ensure smooth data integration. Optimize application performance and implement robust security practices. Design scalable and efficient data models; work with relational and NoSQL databases. Implement and maintain CI/CD pipelines using tools like Docker, Git, Jenkins, or GitHub Actions. Collaborate with front-end developers, DevOps engineers, and product managers to deliver end-to-end solutions. Integrate and deploy ML models and AI features in production environments (a strong plus). Write clean, modular, and testable code following best practices. Troubleshoot, debug, and upgrade existing systems. Required Skills and Qualifications: Strong proficiency in Python and Django framework. Experience with PostgreSQL , MongoDB , or MySQL . Familiarity with Docker , Gunicorn , Nginx , and CI/CD pipelines. Experience with machine learning and deep learning concepts. Exposure to Generative AI , Transformers , Agentic Frameworks , and Fine-Tuning techniques . Hands-on experience with PyTorch or TensorFlow (PyTorch preferred). Ability to translate ML/AI solutions into production-ready APIs or services. Strong problem-solving and debugging skills. Nice to Have: Knowledge of FastAPI or Flask. Experience deploying models via TorchServe or ONNX. Familiarity with MLOps practices and tools like MLflow, DVC, or SageMaker. If you're passionate about backend development and excited to work at the intersection of software engineering and AI innovation , we’d love to hear from you.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: Develop and execute the vision for Generative AI services enablement and solution delivery on United AI Studio (enterprise ML platform) to enable thousands of developers to build their own applications Stay up to date with latest Generative AI technologies and literature recommending solutions to improve business goals Create and manage best practices for us of Generative AI that will ensure secure, consistent, and efficient use of resources across the UHG enterprise Evangelize the benefits of generative AI through proofs-of-concept and demos to drive adoption for employees and functional roles across the UHG enterprise including technology, operations, marketing, legal, compliance, people team, internal infrastructure, and more Mentor AI/ML entering teams in both understanding the details of ML literature to ensuring the delivery of AI/ML projects Collaborate with cross-functional teams to determine applicability of AI to business problems Closely collaborate with the Responsible Use of AI (RUAI) team to ensure that the delivered solutions are compliant with the company policies and standards Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelor’s degree in computer science, Math, Statistics, or a related STEM field with equivalent experience 15+ years of experience in a technical engineering role including 5+ years focused on AI/ML solutions delivery Experience leading and implementing AI/ML projects from ideation to delivery and evaluation Working knowledge of Software Development tools and practices including DevOps and CI/CD tools (Git, Jenkins, Docker, Kubernetes, etc.) Proficiency in cloud platforms and services (Azure, AWS, GCP, etc.) Proficiency in Gen AI solution pipeline engineering, RAG, Evaluations Proficiency in Large Language Modeling and Transformer Architectures (BERT, GPT, etc.) Proficiency in AI/ML engineering systems with Python Proficiency of AI/ML frameworks and tools (MLFlow, TensorFLow, PyTorch, JAX) Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concept and results to technical and non-technical audiences Preferred Qualifications: Master’s in computer science, Mathematics, Statistics, or a related STEM discipline Experience in healthcare (AI) Experience working with cross-functional and distributed teams in a global and diverse environment Experience in mentoring and coaching AI/ML talent Experience in establishing AI/ML best practices, standards, and ethics A proven track record of delivering high-impact AI/ML solutions for real-world problems and use cases A portfolio of AI/ML publications, patents, or awards Demonstrated superior written and verbal presentation skills with a wide range of size and types of audiences including executive leadership At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

We are seeking a highly skilled AI Engineer with a strong foundation in machine learning, deep learning, cloud platforms , and computer vision to join our innovative tech team. You’ll design and implement scalable AI/ML pipelines, automate workflows, train and optimize models, and deploy solutions on cloud infrastructure. This is an opportunity to shape the future of intelligent systems across industries. Key Responsibilities: Design, develop, and deploy ML/DL models for various applications, including computer vision and predictive analytics. Build data pipelines and model training workflows on cloud platforms such as AWS, Azure, or GCP. Automate model retraining, evaluation, and deployment processes using MLOps best practices. Collaborate with cross-functional teams (data engineers, product managers, developers) to define project requirements and deliver AI-powered features. Develop and fine-tune custom algorithms tailored to specific domain problems. Integrate AI solutions into existing systems using APIs, containers, and cloud-native tools. Conduct data preprocessing, exploratory data analysis, and feature engineering. Research and evaluate the latest AI trends, tools, and frameworks to recommend enhancements. Write clear, maintainable, and efficient code with documentation for reproducibility and scaling. Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related fields. 3+ years of hands-on experience in building and deploying machine learning/deep learning models. Strong programming skills in Python and frameworks like TensorFlow, PyTorch, OpenCV, Scikit-learn. Experience with computer vision libraries (OpenCV, YOLO, Detectron2, etc.). Proficiency in cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML Studio). Experience with Docker, Kubernetes, or other orchestration tools. Familiarity with MLOps tools like MLflow, DVC, Kubeflow, or Airflow. Solid understanding of algorithms, data structures, and model optimization techniques. Exposure to RESTful APIs and real-time inference systems. Strong analytical, problem-solving, and communication skills. Nice to Have: Experience with NLP models and transformers (e.g., Hugging Face). Experience deploying models at scale in production environments. Knowledge of CI/CD pipelines for AI applications. Publications or contributions to open-source AI projects. Why Join Us? Job Type: Permanent Pay: ₹20,000.00 - ₹50,000.00 per month Work Location: In person

Role Title: AI Platform Engineer Location: Bangalore (In Person in office when required) Part of the GenAI COE Team Key Responsibilities Platform Development and Evangelism: Build scalable AI platforms that are customer-facing. Evangelize the platform with customers and internal stakeholders. Ensure platform scalability, reliability, and performance to meet business needs. Machine Learning Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining. Implement A/B testing of models. Design APIs for model inferencing at scale. Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. LLM Serving and GPU Architecture: Serve as an SME in LLM serving paradigms. Possess deep knowledge of GPU architectures. Expertise in distributed training and serving of large language models. Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. Model Fine-Tuning and Optimization: Demonstrate proven expertise in model fine-tuning and optimization techniques. Achieve better latencies and accuracies in model results. Reduce training and resource requirements for fine-tuning LLM and LVM models. LLM Models and Use Cases: Have extensive knowledge of different LLM models. Provide insights on the applicability of each model based on use cases. Proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. DevOps and LLMOps Proficiency: Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Skill Matrix LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery. Cloud Knowledge: AWS/Azure/GCP Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert Proficient in Python, SQL, Javascript Job Type: Full-time Work Location: In person