977 Mlops Jobs

As a Senior Machine Learning/AI Manager at CDK, you will lead and mentor a team of scientists and engineers to deliver high-quality ML/AI solutions. You will own the full ML lifecycle from data exploration and feature engineering to model deployment and monitoring. Your role will involve architecting and implementing models for recommendation systems, classification, forecasting, and generative AI use-cases. Collaborating cross-functionally with product, engineering, and MLOps teams will be crucial to translate business needs into scalable ML solutions. Utilizing LLMs and Retrieval-Augmented Generation (RAG) to build intelligent customer experiences will be a key aspect of your responsibilities. Additionally, you will champion model performance, interpretability, and reproducibility across varied domains. Your contribution to reusable AI/ML tooling, pipelines, and best practices will play a significant role in improving development velocity. **Key Responsibilities:** - Lead and mentor a team of scientists and engineers - Own the full ML lifecycle - Architect and implement models for various AI use-cases - Collaborate cross-functionally with product, engineering, and MLOps teams - Leverage LLMs and Retrieval-Augmented Generation - Champion model performance, interpretability, and reproducibility - Contribute to reusable AI/ML tooling and best practices **Qualifications Required:** - Masters or PhD in Computer Science, Machine Learning, Statistics, or related field - 5+ years of hands-on experience developing and deploying ML models at scale - 2+ years of experience managing or mentoring data scientists or ML engineers - Proficiency in Python and familiarity with languages like Java - Solid foundation in ML techniques including regression, classification, deep learning, and collaborative filtering - Experience with model deployment tools and cloud ML platforms - Strong communication skills; ability to present complex ideas to technical and non-technical stakeholders At CDK, inclusion and diversity are fundamental values that inspire meaningful connections to people, customers, and communities. The company fosters an open, curious environment that encourages different views, allowing everyone to be their best selves and make a positive impact.,

As an experienced AI Analytics Engineer with expertise in Azure DevOps, your role will involve designing, implementing, and optimizing data pipelines, machine learning models, and analytics solutions. You will be responsible for bridging the gap between data science, engineering, and DevOps practices to deliver scalable and production-ready AI/ML solutions. Key Responsibilities: - Design, develop, and deploy AI/ML models and analytics workflows. - Build and manage end-to-end CI/CD pipelines in Azure DevOps for data and ML projects. - Automate data ingestion, preprocessing, model training, testing, and deployment. - Monitor model performance and implement retraining pipelines. - Work closely with data scientists, data engineers, and business stakeholders to translate requirements into scalable solutions. - Ensure solutions are secure, cost-optimized, and highly available on Azure. - Perform root cause analysis and continuous improvement for production issues. Qualifications Required: - Hands-on experience with Azure DevOps (pipelines, repos, artifacts, boards). - Strong programming skills in Python or R for AI/ML development. - Experience with Azure Machine Learning, Databricks, Synapse, Data Factory. - Good understanding of MLOps principles and tools. - Strong knowledge of data visualization and analytics (Power BI a plus). - Familiarity with containerization (Docker, Kubernetes) for deploying ML workloads. - Experience with version control (Git) and agile development practices. In addition to the above details, the job description also emphasizes the importance of the following soft skills: - Excellent communication and collaboration skills. - Ability to translate technical insights into business value. - Strong analytical thinking and attention to detail. (Note: Any additional details of the company were not provided in the job description),

As a Lead AI Developer at Aumento Technologies & Consulting Services Pvt Ltd, you will play a crucial role in bridging business requirements with cutting-edge AI solutions. You will independently design, develop, and deploy enterprise-grade AI systems, including RAG (Retrieval-Augmented Generation) based applications. **Key Responsibilities:** - Collaborate with business stakeholders to identify and scope AI/ML/GenAI opportunities - Lead development of RAG-based AI solutions, integrating LLMs with enterprise data sources - Design and implement data pipelines, embeddings, and vector databases for retrieval-based systems - Build and optimize machine learning, deep learning, NLP, and generative AI models - Deploy AI solutions into production on cloud platforms (SAP BTP AI Core, Azure ML, AWS Sagemaker, GCP Vertex AI) - Establish best practices in MLOps (CI/CD, monitoring, model retraining, governance) - Mentor junior AI developers and contribute to reusable AI accelerators **Required Skills & Experience:** - Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or related field - 6+ years of experience in AI/ML development, with 2+ years in a lead/architect role - Strong programming in Python and experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) - Hands-on expertise in Generative AI, RAG pipelines, vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) - Experience with LLM integration (OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex, etc.) - Strong knowledge of NLP techniques: embeddings, transformers, summarization, question answering - Experience with cloud-based AI development (SAP BTP AI Core preferred, Azure, AWS, GCP) - Understanding of MLOps & model lifecycle management - Ability to articulate business requirements and convert them into scalable AI solutions **Good to Have:** - Experience integrating AI with SAP ecosystem (SAC, BTP, DataSphere, Integration Suite) - Domain exposure in Manufacturing, CPG industries, Pharma, Automotive - Knowledge of prompt engineering and fine-tuning LLMs - Experience in data security, governance, and responsible AI If you are passionate about building AI solutions that blend machine learning, generative AI, and RAG for real-world impact, do not hesitate to apply. Join us to lead cutting-edge AI & GenAI initiatives across industries and be part of an entrepreneurial, collaborative work environment with competitive compensation and fast-track growth opportunities.,

As a Data Scientist at Texas Instruments, you will be a key player in the Demand Analytics team, focusing on shaping and executing demand planning and inventory buffer strategies. Working alongside a team of technical professionals, including application developers, system architects, data scientists, and data engineers, you will be responsible for solving complex business problems through innovative solutions that drive tangible business value. Your role will involve portfolio management for demand forecasting algorithms, generation of inventory buffer targets, segmentation of products, simulation/validation frameworks, and ensuring security and interoperability between capabilities. Key Responsibilities: - Engage strategically with stakeholder groups to align with TI's business strategy and goals - Communicate complex technical concepts effectively to influence final business outcomes - Collaborate with cross-functional teams to identify and prioritize actionable insights - Build scalable and modular technology stacks using modern technologies - Conduct simulations with various models to determine the best fit of algorithms - Research, experiment, and implement new approaches and models in line with business strategy - Lead data acquisition and engineering efforts - Develop and apply machine learning, AI, and data engineering frameworks - Write and debug code for complex development projects - Evaluate and determine the best modeling techniques for different scenarios Qualifications: Minimum requirements: - MS or PhD in a quantitative field or equivalent practical experience - 8+ years of professional experience in data science or related roles - 5+ years of hands-on experience developing and deploying time series forecasting models - Deep understanding of supply chain concepts like demand forecasting and inventory management - Proficiency in Python and core data science libraries - Experience taking machine learning models from prototype to production Preferred qualifications: - Experience with MLOps tools and platforms - Practical experience with cloud data science platforms - Familiarity with advanced forecasting techniques and NLP - Strong SQL skills and experience with large-scale data warehousing solutions About Texas Instruments: Texas Instruments is a global semiconductor company that designs, manufactures, and sells analog and embedded processing chips for various markets. At TI, we are passionate about creating a better world by making electronics more affordable through semiconductors. Our commitment to innovation drives us to build technology that is reliable, affordable, and energy-efficient, enabling semiconductors to be used in electronics everywhere. Join TI to engineer your future and collaborate with some of the brightest minds to shape the future of electronics. Embrace diversity and inclusion at TI, where every voice is valued and contributes to our strength as an organization. If you are ready to make an impact in the field of data science, apply to join our team at Texas Instruments.,

8-10 yrs in AI/ML Tools and packages using Databrick Models. Exposure to Healthcare data projects and MLOps tools Responsible for migrating existing machine learning models and pipelines to a new platform, ensuring continuity and performance

8-10 yrs in AI/ML Tools and packages using Databrick Models. Exposure to Healthcare data projects and MLOps tools Responsible for migrating existing machine learning models and pipelines to a new platform, ensuring continuity and performance

As a Software Engineer at Visa's VAS Innovation team, you will play a crucial role in developing cutting-edge solutions to enhance the capabilities of Value-Added Services (VAS) platform. Your responsibilities will include: - Engaging in the design, development, and implementation of innovative software solutions, such as generative AI and modern integration patterns. - Collaborating with cross-functional teams to deliver complex projects that integrate emerging technologies with existing platforms. - Engaging in continuous learning and development to enhance your skills and knowledge. - Developing client-focused solutions with a mindset to deliver exceptional value and innovation. - Contributing to the design and development of APIs that enhance the integration of VAS applications, platforms, and solutions. - Participating in the advancement of the technology modernization roadmap by adopting best-in-class technology solutions. - Continuously assessing and improving technology stacks, development processes, and methodologies to enhance productivity and quality. - Adhering to industry best practices in software development and emphasizing quality, security, performance, scalability, and resilience. - Implementing best engineering practices and automating software development, testing, and deployment processes to focus on continuous improvement. - Supporting incident management, change, and problem management processes to ensure high availability and reliability of services. Qualifications: Basic Qualifications: - 3 or more years of relevant work experience with a bachelor's degree or 2 years with an Advanced Degree (Masters/PhD in Engineering/Computer Science). - Self-driven and willing to work across technologies/languages. - Expert-level skills in Java and Python with skills in C++ and C# being a bonus. - In-depth understanding of NLP including tokenization, word embeddings, and basic sequence models. - Proficiency in implementing and fine-tuning AI models using popular frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Ability to work with large datasets and perform exploratory data analysis. - Experience with data preprocessing, feature engineering, and model evaluation techniques. - Expertise in handling multi-threading, concurrency, and error-handling. - Demonstrated proficiency in troubleshooting, root-cause analysis, application design, and implementing large components for enterprise projects. - Knowledge of version control, CI/CD pipelines, and best practices for ML model deployment. Preferred Qualifications: - Understanding of enterprise security, certificate management, etc. - Hands-on experience with Jenkins and container deployment architecture. - Experience using OAuth2.0, SSO, and authentication methods/protocols. - Expertise in application security, SSDLC, and knowledge of cryptography fundamentals.,

Lead Data Scientist - Generative AI & LLMs Location: Hyderabad Notice Period: Immediate to 30days About the Role As a Lead Data Scientist, you will drive the architecture, design, and delivery of GenAI solutions, focusing on LLM and vLLM fine-tuning, data strategy, and model performance. This is a strategic, leadership-oriented role requiring a deep technical foundation and strong stakeholder collaboration. Key Responsibilities Lead design and implementation of LLM-powered GenAI platforms and document intelligence products. Architect and own data pipelines for fine-tuning large language models using large- scale datasets. Guide and mentor data science teams on LLM training best practices, evaluation, and deployment. Optimize model inference (latency, throughput) using vLLM, quantization, or model distillation techniques. Own the model lifecycle from experimentation to production-grade deployment. Partner with engineering/product teams to translate business needs into scalable AI solutions. Required Skills 7+ years in data science, with 3+ years focused on NLP and LLMs. Proven expertise in fine-tuning large-scale models on enterprise or open datasets. Hands-on with vLLM, PEFT (Parameter Efficient Fine Tuning), LoRA, and quantization strategies. Experience optimizing inference pipelines for production environments. Strong coding background in Python, PyTorch, and scalable ML architectures. Deep understanding of model alignment, evaluation strategies, and generative QA tasks. Leadership Skills Ability to lead cross-functional teams across data science, MLOps, and software engineering. Experience mentoring junior team members and reviewing model design/code. Strong communication skills to influence technical and non-technical stakeholders.

Develop and optimize AI models for insurance use cases, apply data science for predictive insights, innovate with latest AI, integrate with engineering teams, and ensure scalable, cost-efficient, reliable deployment and maintenance. Required Candidate profile Hands-on with GenAI, LLMs, prompt engineering, and fine-tuning; skilled in Python, TensorFlow, PyTorch; strong in data science, predictive analytics, and MLOps for scalable AI deployment.

DevOps Engineer Business Group: Technology Primary Work Location: EEEC Pune, India Job Summary: We are seeking a highly skilled and hardworking DevOps Engineer to join our dynamic team. Candidates should have a minimum of 3 to 5 years recent experience in Docker, Docker Compose, Kubernetes (AKS), MongoDB, SQL Server, Linux, and Azure cloud and platform administration. In this Role, Your Responsibilities Will Be: Responsible for app containerization & deployments for various sprint/QA/validated releases, Customer specific deployments, Installation support for customers, support for Dev/QA/Val/Performance testing. Responsible for building and maintaining Repos/CI/CD pipelines. Maintain the enterprise infrastructure platforms on Azure cloud. Who You Are: You anticipate customer needs and provide services that are beyond customer expectations. You readily distinguish between what is relevant and what is unimportant to make sense of complex situations. You achieve and are consistently known as a top performer. For This Role, You Will Need: Bachelors degree or equivalent in Computer Science, Computer Engineering, MSc / MCA (Computer Science/ IT) is required. Overall relevant experience of around 3 to 5 Years Work experience in designing, deploying and maintaining Kubernetes clusters in production environments Implement autoscaling, rolling updates. Build secure, scalable CI/CD pipelines and enforce container security best practices across environments. Containerize applications using Docker and automate infrastructure provisioning with tools like Terraform Diagnose and resolve infrastructure issues, optimize resource usage, and implement disaster recovery strategies. Work closely with development, QA, and security teams while maintaining clear documentation of systems and processes. Working experience in Microservices based Architecture. Working experience in Platform & Cloud Administration Preferred Qualifications that Set You Apart: Experience working in Agile development methodology. Working experience in enterprise SSO integration (SAML, OAuth) & Azure DevOps administration Configuration and managing Neo4j Clusters Building and deploying MLOps Solutions A drive towards automating repetitive tasks (e.g., scripting via Bash, Python etc.) Good interpersonal and communication skills Our Offer to You: By joining Emerson, you will be given the opportunity to make a difference through the work you do. Emerson's compensation and benefits programs are designed to be competitive within the industry and local labor markets . We also offer a comprehensive medical and insurance coverage to meet the needs of our employees. We are committed to creating a global workplace that supports diversity, equity and embraces inclusion . We welcome foreign nationals to join us through our Work Authorization Sponsorship . We attract, develop, and retain exceptional people in an inclusive environment, where all employees can reach their greatest potential . We are dedicated to the ongoing development of our employees because we know that it is critical to our success as a global company. We have established our Remote Work Policy for eligible roles to promote Work-Life Balance through a hybrid work set up where our team members can take advantage of working both from home and at the office. Safety is paramount to us, and we are relentless in our pursuit to provide a Safe Working Environment across our global network and facilities. Through our benefits, development opportunities, and an inclusive and safe work environment, we aim to create an organization our people are proud to represent. Our Commitment to Diversity, Equity & Inclusion At Emerson, we are committed to fostering a culture where every employee is valued and respected for their unique experiences and perspectives. We believe a diverse and inclusive work environment contributes to the rich exchange of ideas and diversity of thoughts, that inspires innovation and brings the best solutions to our customers. This philosophy is fundamental to living our companys values and our responsibility to leave the world in a better place. Learn more about our Culture & Values and about Diversity, Equity & Inclusion at Emerson . If you have a disability and are having difficulty accessing or using this website to apply for a position, please contact: idisability.administrator@emerson.com . WHY EMERSON Our Commitment to Our People At Emerson, we are motivated by a spirit of collaboration that helps our diverse, multicultural teams across the world drive innovation that makes the world healthier, safer, smarter, and more sustainable. And we want you to join us in our bold aspiration. We have built an engaged community of inquisitive, dedicated people who thrive knowing they are welcomed, trusted, celebrated, and empowered to solve the worlds most complex problems for our customers, our communities, and the planet. Youll contribute to this vital work while further developing your skills through our award-winning employee development programs. We are a proud corporate citizen in every city where we operate and are committed to our people, our communities, and the world at large. We take this responsibility seriously and strive to make a positive impact through every endeavor. At Emerson, youll see firsthand that our people are at the center of everything we do. So, lets go. Lets think differently. Learn, collaborate, and grow. Seek opportunity. Push boundaries. Be empowered to make things better. Speed up to break through. Lets go, together. ABOUT EMERSON Emerson is a global leader in automation technology and software. Through our deep domain expertise and legacy of flawless execution, Emerson helps customers in critical industries like life sciences, energy, power and renewables, chemical and advanced factory automation operate more sustainably while improving productivity, energy security and reliability. With global operations and a comprehensive portfolio of software and technology, we are helping companies implement digital transformation to measurably improve their operations, conserve valuable resources and enhance their safety. We offer equitable opportunities, celebrate diversity, and embrace challenges with confidence that, together, we can make an impact across a broad spectrum of countries and industries. Whether youre an established professional looking for a career change, an undergraduate student exploring possibilities, or a recent graduate with an advanced degree, youll find your chance to make a difference with Emerson. Join our team lets go!

Were seeking a visionary Technical Architect with deep expertise in Data Science and Generative AI to lead the design and implementation of cutting-edge AI solutions. This role blends strategic thinking with hands-on technical leadership, enabling transformative innovation across industries. You’ll architect scalable systems, guide cross-functional teams, and shape the future of AI-powered products—from intelligent automation to synthetic data generation and beyond. Key Responsibilities Architect AI Solutions: Design end-to-end architectures for GenAI and data science platforms, including model pipelines, data lakes, and deployment strategies Lead Technical Strategy: Define technical roadmaps for AI/ML initiatives aligned with business goals Model Development Oversight: Guide development of LLMs, transformers, and other generative models using frameworks like PyTorch, TensorFlow, and Hugging Face Data Engineering Collaboration: Partner with data engineers to ensure robust data pipelines, feature stores, and real-time data ingestion MLOps & Deployment: Implement CI/CD pipelines for ML models, containerization (Docker/Kubernetes), and cloud-native deployments (Azure, AWS, GCP) Security & Ethics: Ensure responsible AI practices, model interpretability, and compliance with data privacy regulations Mentorship & Leadership: Coach data scientists, ML engineers, and developers on best practices and emerging technologies Stakeholder Engagement: Translate complex technical concepts into business value for executives and clients Required Skills & Qualifications Proven experience as a Technical Architect or Principal Engineer in AI/ML domains Strong proficiency in Python, SQL, and cloud platforms (Azure preferred) Expertise in GenAI frameworks (e.g., Lang Chain, OpenAI APIs, Retrieval-Augmented Generation) Solid understanding of data science workflows, statistical modeling, and feature engineering Experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and embedding techniques Familiarity with prompt engineering, fine-tuning LLMs, and RLHF Excellent communication and leadership skills Bachelor’s or Master’s degree in Computer Science, Data Science, or related field (PhD preferred) Preferred Qualifications Experience with multimodal AI (text, image, audio) Contributions to open-source AI projects or publications Certifications in cloud architecture or AI/ML (e.g., Azure AI Engineer, AWS Machine Learning Specialty)

What You Will Do: Design, build, and maintain end-to-end MLOps pipelines for ML model training, testing, and deployment. Collaborate with Data Scientists to productionize ML models in Azure ML and Azure Databricks. Implement CI/CD pipelines for ML workflows using Azure DevOps, GitHub Actions, or Jenkins. Automate infrastructure provisioning using IaC tools (Terraform, ARM templates, or Bicep). Monitor and manage deployed models using Azure Monitor, Application Insights, and MLflow. Implement best practices in model versioning, model registry, experiment tracking, and artifact management. Ensure security, compliance, and cost optimization of ML solutions deployed on Azure. Work with cross-functional teams (Data Engineers, DevOps Engineers, Data Scientists) to streamline ML delivery. Develop monitoring/alerting for ML model drift, data drift, and performance degradation. What You Need: Required Skills • 5-10 years of experience in programming: Python (must), SQL;. MLOps/DevOps Tools: MLflow, Azure DevOps, GitHub Actions, Docker, Kubernetes (AKS). • Azure Services: Azure ML, Azure Databricks, Azure Data Factory, Azure Storage, Azure Functions, Azure Event Hubs. • CI/CD: Experience designing pipelines for ML workflows. IaC: Terraform, ARM templates, or Bicep. • Data Handling: Experience with Azure Data Lake, Blob Storage, and Synapse Analytics. • Monitoring & Logging: Azure Monitor, Prometheus/Grafana, Application Insights. Strong knowledge of ML lifecycle (data preprocessing, model training, deployment, monitoring). Preferred Skills: • Experience with Azure Kubernetes Service (AKS) for scalable model deployment. • Knowledge of feature stores and distributed training frameworks. Familiarity with RAG (Retrieval Augmented Generation) pipelines and LLMOps. • Azure certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, or Azure DevOps Engineer Expert.

As a Data Science and AI / ML professional at LTIMindtree, you will play a crucial role in leveraging digital technologies to drive innovation and growth for our clients. With over 6 years of experience in the field, you will be expected to have a deep understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Your expertise in data frameworks like Hadoop, business intelligence tools like Tableau, and Cloud native skills will be essential in delivering superior business outcomes. Key Responsibilities: - Utilize your knowledge of SQL and Python, with familiarity in Scala, Java, or C++ as an asset, to develop innovative AI solutions - Apply your analytical mind and strong math skills in statistics and algebra to solve complex business challenges - Work with common data science toolkits such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy, etc., with expertise in at least one being highly desirable - Leverage your experience in NLP, NLG, and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc., to drive transformative projects - Communicate effectively and present your findings with great clarity, thriving in a fast-paced team environment - Utilize AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR, etc., to scale your solutions - Apply your expertise in NoSQL databases such as MongoDB, Cassandra, HBase, Vector databases to handle large datasets effectively - Demonstrate a good understanding of applied statistics skills like distributions, statistical testing, regression, etc., to derive valuable insights for the business Qualifications Required: - More than 6 years of experience in Data Science and AI / ML domain - Excellent understanding of machine learning techniques and algorithms - Experience using business intelligence tools and data frameworks - Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset - Strong math skills (e.g., statistics, algebra) - Experience with common data science toolkits - Great communication and presentation skills - Experience with AIML and Big Data technologies - Experience with NoSQL databases Please note that the mentioned qualifications, skills, and experiences are mandatory for the role at LTIMindtree.,

Role Overview: You will be responsible for designing, building, and deploying Generative AI models using foundational models like GPT, BERT, LLaMA, PaLM, etc. Additionally, you will develop scalable GenAI applications, integrate them with enterprise systems using APIs and SDKs, and fine-tune large language models (LLMs) for domain-specific use cases. You will also design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure, collaborate with data scientists to productionize ML models, and automate deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools. Furthermore, you will ensure security, compliance, and governance of ML workflows and data, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures. Key Responsibilities: - Design, build, and deploy Generative AI models using models like GPT, BERT, LLaMA, PaLM - Develop scalable GenAI applications and integrate with enterprise systems using APIs and SDKs - Fine-tune and optimize large language models (LLMs) for domain-specific use cases - Design, implement, and manage end-to-end machine learning pipelines on Microsoft Azure - Collaborate with data scientists to productionize ML models using best practices in Azure MLOps - Automate the deployment and monitoring of models using CI/CD pipelines and Azure DevOps tools - Implement scalable model training, validation, and deployment workflows in the cloud - Monitor model performance in production, retrain models as needed, and ensure security, compliance, and governance of ML workflows and data - Develop Python scripts and tools to automate tasks, troubleshoot and optimize ML workflows, and document architecture, processes, and operational procedures Qualifications Required: - Hands-on experience with transformer-based models (e.g., GPT, BERT, LLaMA, etc.) - Familiarity with tools like LangChain, LlamaIndex, Haystack, etc. - Experience in prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning - Proven experience in MLOps, specifically with Azure services - Strong programming skills in Python - Experience with Hugging Face Transformers, PyTorch or TensorFlow - REST APIs and/or gRPC for model integration - Experience with Azure Databricks, Azure Machine Learning, Azure OpenAI - Familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch) - Experience building and managing CI/CD pipelines for ML models using Azure DevOps or equivalent tools - Building REST APIs for ML inference using frameworks like FastAPI or Flask - Understanding of containerization technologies like Docker and orchestration using Kubernetes - Knowledge of machine learning lifecycle management, model versioning, and deployment strategies - Experience with data engineering, data pipelines, and ETL processes on Azure - Familiarity with monitoring tools and logging frameworks for production systems - Strong problem-solving skills and ability to work in a collaborative, fast-paced environment,

As an experienced consulting professional in the field of Data Science or AI/ML Engineering, you will be responsible for understanding solutions, industry best practices, and implementing Oracle products and technology to meet customer needs. You will operate independently to deliver high-quality work products to engagements, applying Oracle methodology, company procedures, and leading practices. **Key Responsibilities:** - Lead end-to-end AI/ML solution design and production deployment - Specialize in Generative AI, LLMs, NLP, and AI agent development - Expertise in Python and modern ML/NLP frameworks such as HuggingFace, LangChain, PyTorch, TensorFlow - Fine-tune LLMs for domain-specific applications like Q&A systems, auto-documentation, and predictive insights - Build, scale, and optimize AI systems on OCI with knowledge of hybrid/multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines - Familiarity with MLOps, model governance, and CI/CD for ML workflows - Excellent communication and stakeholder management skills to bridge the gap between technical and executive teams **Qualifications & Experience:** - 12-15 years of total experience, with a minimum of 5 years in Data Science or AI/ML Engineering roles - Proven track record in AI/ML solution design and deployment - Expertise in Python and modern ML/NLP frameworks - Hands-on experience with AI systems on OCI and knowledge of multi-cloud architectures - Strong knowledge of machine learning algorithms, prompt engineering, and model governance - Experience in stakeholder engagement, program oversight, and solution design **Additional Details:** The company is committed to an inclusive culture that celebrates diverse insights and perspectives, fostering an environment that inspires thought leadership and innovation. Oracle offers a competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability, including Medical, Life Insurance, Retirement Planning, and more. The company encourages employees to engage in giving back to communities and values diversity and inclusion in the workforce. If you are looking for a challenging role where you can leverage your expertise in AI/ML engineering to drive innovative solutions and work in a diverse and inclusive environment, this position at Oracle might be the perfect fit for you.,

You will be responsible for playing a crucial role as a Principal Software Maintenance Engineer at Red Hat, focusing on enhancing the long-term product experience for Red Hat OpenShift AI (RHOAI) customers. Your primary responsibilities will include: - Collaborating closely with Product Engineering to deliver extended product maintenance work, addressing bugs and Common Vulnerabilities and Exposures (CVEs) in the extended life streams of Red Hat OpenShift AI. - Driving all aspects of Red Hat OpenShift maintenance for a specific subset of product components related to software development that goes beyond the standard maintenance phase of Red Hat OpenShift AI minor releases. - Contributing to the patch review process, designing and developing backports, creating test automation and test plans, and developing automation tools to enhance the efficiency, flexibility, and quality of Red Hat's patch delivery to customers. - Providing technical leadership for engineers within the team. In addition to the above responsibilities, you will also be expected to: - Contribute to the development of new Red Hat OpenShift AI product maintenance offerings, with the goal of establishing Red Hat as a global leader in long-term product experience. - Explore and experiment with emerging AI technologies relevant to software development, identifying opportunities to integrate new AI capabilities into existing workflows and tooling. - Collaborate with cross-functional teams to identify AI integration opportunities within the software development lifecycle, driving continuous improvement and innovation in engineering practices. - Ensure a special focus on meeting non-functional requirements such as security, resiliency, and maintainability. - Write complex integration tests, work with quality engineers to ensure product quality, and utilize CI/CD best practices for delivering solutions as productization efforts into RHOAI. - Contribute to a culture of continuous improvement by sharing recommendations and technical knowledge with team members. - Collaborate with product management, other engineering teams, and cross-functional teams to analyze and clarify business requirements effectively. - Communicate with stakeholders and team members to ensure proper visibility of development efforts. - Conduct thoughtful and timely code reviews, diagnose the root cause of failures, and maintain clear and comprehensive documentation for tests, test cases, and testing procedures. - Stay updated on emerging testing tools, technologies, and best practices. To excel in this role, you should possess the following qualifications: - Development expertise in Golang and/or Python. - Advanced experience in testing applications in Golang and/or Python. - Advanced experience in Kubernetes, OpenShift, or other cloud-native technologies. - Advanced experience in React, Typescript. - Strong understanding of CI/CD practices and experience working with tools like Jenkins, GitHub Actions, GitLab CI, or similar. - Ability to quickly learn and guide others on using new tools and technologies. - Autonomous work ethic, thriving in a dynamic, fast-paced environment. - Experience with source code management tools such as Git. - Hands-on experience in release pipeline preparation and Builds creation. - Hands-on experience in Builds validation and smoke testing, including upgrade testing. - Technical leadership acumen in a global team environment. - Strong problem-solving and troubleshooting skills with Root Cause Analysis experience. - Ability to work independently in a fast-paced, ever-changing environment. - Excellent written and verbal communication skills. - Experience with Agile/Scrum methodologies. Additionally, the following qualifications would be considered a plus: - Practical experience and technical prowess, prioritized over a Bachelor's degree or higher in computer science or a related discipline. - Knowledge of the AI and machine learning landscape, including basic MLOps concepts. - Understanding of how Open Source and Free Software communities operate. - Experience with public cloud services such as AWS, GCE, Azure. - Experience working with or deploying MLOps platforms. Red Hat is a global leader in enterprise open-source software solutions, fostering an inclusive environment that values transparency, collaboration, and innovation. Join Red Hat in celebrating diversity and inclusivity, where all voices are heard and celebrated.,

Role Overview: At Ramboll Tech, as a Lead Machine Learning Engineer, you will be responsible for creating cutting-edge AI solutions while mentoring others and fostering a culture of collaboration and growth. Your role will involve shaping the technical roadmap, contributing to the implementation of best practices, and working with global teams to deliver impactful AI solutions. Key Responsibilities: - Define architectural patterns for scalable LLM pipelines, ensuring robust versioning, monitoring, and adherence to best practices. - Drive the integration of external knowledge bases and retrieval systems to augment LLM capabilities. - Research and develop effective RAG architectures and technologies for organizing complex domain-specific data. - Explore and benchmark state-of-the-art LLMs, tuning, adaptation, and training for performance and cost efficiency. - Incorporate recent trends like instruction tuning, RLHF, or LoRA fine-tuning for domain customization. - Analyze models for quality, latency, sustainability metrics, and cost, implementing improvements for better outcomes. - Define and own the ML-Ops for your Pod. - Develop experiments for model evaluation and improvement, aligned with evolving industry standards. - Establish scalable coding standards and best practices for maintainable and production-ready systems. - Mentor ML engineers to foster their personal growth. Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - Minimum 5 years of experience implementing machine learning projects. - At least 2 years in a senior or lead role. - Demonstrated expertise in integrating modern LLMs into production systems. - Proven leadership in driving technical projects to successful completion in agile environments. - Strong communication skills to align technical solutions with business goals. - Ability to mentor and foster innovation within the team. - Strong expertise in building Retrieval-Augmented Generation (RAG) architectures and integrating with vector and graph databases. - In-depth experience with modern Transformer-based LLMs. - Demonstrated ability to fine-tune and optimize LLMs for quality, latency, sustainability, and cost-effective performance. - Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain. - Experience with containerization tools (e.g. Docker, Kubernetes) and workflow management tools. - Hands-on experience with (preferably Azure) Cloud environments for scalable AI deployment. - Experience with relational (SQL), NoSQL databases. - Familiarity with platforms like Snowflake or Databricks. Additional Details of the Company: At Ramboll Tech, the team culture is crucial, focusing on exchanging ideas, supporting each other, and fostering a strong team spirit. The company values diversity and aims to continuously learn and grow from one another. Ramboll is a global architecture, engineering, and consultancy firm committed to creating a livable world where people thrive in healthy nature. Ramboll Tech accelerates innovation and digital transformation within the company and collaborates on AI projects. The company is dedicated to equality, diversity, and inclusion, providing an inclusive work environment where everyone can flourish and reach their potential.,

As an AI & Software Engineer in the Artificial Intelligence & Development team, you will play a crucial role in contributing to the future of the Energy Transformation industry. You will collaborate with teams to implement and adapt AI algorithms across various projects such as document understanding, predictive maintenance, defect detection by computer vision, control, and robotics. Your responsibilities will include developing and integrating software components for AI applications, testing software components according to customer and technical requirements, verifying and validating AI software applications, and supporting the scale-up and deployment of AI applications. You will also be involved in ensuring the availability and relevance of internal and external data sources, leading new data collection activities, and cleaning and validating data. To be successful in this role, you should have 2-6 years of relevant experience in software programming languages such as Python, Java, and C++. You should also possess expertise in Software Development and DevOps processes like MLOps, CI/CD, GitHub, and AngularJS. Additionally, experience in containerization, microservices, cloud-based design, architecture, infrastructure design, Machine Learning algorithms, and AI tools like Computer Vision, NLP, and RPA is required. Knowledge of Web Services protocols such as REST, SOAP, API design, databases, Test Driven Development, and Agile Development methods will be beneficial for this role. In this position, you will have the opportunity to work remotely from home or any other location occasionally and enjoy flexible working hours to accommodate your most productive times. The company values diversity and individuality, offering contemporary work-life balance policies, comprehensive private medical care options, life insurance, disability programs, tailored financial programs, and additional elected or voluntary benefits. Baker Hughes is an energy technology company that provides innovative solutions to energy and industrial customers globally. With a presence in over 120 countries, the company is committed to making energy safer, cleaner, and more efficient for people and the planet. If you are passionate about Software Development and DevOps practices and want to be part of a team that values innovation and progress, consider joining Baker Hughes to contribute to taking energy forward.,

Role Overview: You will be a part of the Data and Analytics (D&A) team at EY as a Senior Data Scientist. With a minimum of 3-7 years of experience in Data Science and Machine Learning, you will be involved in developing and implementing AI solutions, particularly focusing on NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Your role will be crucial in leveraging your technical expertise to contribute to cutting-edge AI models and systems. Responsibilities: - Contribute to the design and implementation of state-of-the-art AI solutions. - Assist in the development and implementation of AI models and systems, utilizing techniques such as Language Models (LLMs) and generative AI. - Collaborate with stakeholders to identify business opportunities and define AI project goals. - Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. - Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. - Integrate with relevant APIs and libraries like Azure Open AI GPT models and Hugging Face Transformers to enhance generative AI capabilities. - Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. - Utilize vector databases such as Redis and NoSQL databases for efficient handling of large-scale generative AI datasets. - Implement similarity search algorithms to enable efficient retrieval of information from generative AI outputs. - Collaborate with domain experts, stakeholders, and clients to tailor generative AI solutions based on specific business requirements. - Conduct research on advanced AI techniques to enhance performance and efficiency. - Establish evaluation metrics to assess the quality and relevance of generative AI outputs. - Ensure compliance with data privacy, security, and ethical considerations in AI applications. - Utilize data engineering skills for data curation, cleaning, and preprocessing for generative AI applications. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Ph.D. is a plus. - Minimum 3-7 years of experience in Data Science and Machine Learning. - Proficiency in programming languages like Python, R, and frameworks such as TensorFlow or PyTorch. - Strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models. - Familiarity with computer vision techniques. - Experience with cloud platforms like Azure, AWS, or GCP for deploying AI solutions. - Knowledge of trusted AI practices ensuring fairness, transparency, and accountability. - Strong collaboration skills with software engineering and operations teams. - Excellent problem-solving and analytical skills. - Strong communication and interpersonal skills. - Understanding of data privacy, security, and ethical considerations. - Track record of innovation and staying updated with AI research and advancements.,

As a Senior Data Scientist at AuxoAI, you will have the opportunity to lead the design, deployment, and scaling of production-grade ML systems, focusing on AI, machine learning engineering (MLE), and generative AI. Your role will involve a combination of cutting-edge research and production rigor, where you will be responsible for mentoring while building impactful AI applications. Key Responsibilities: - Own the full ML lifecycle, including model design, training, evaluation, and deployment - Design production-ready ML pipelines integrating CI/CD, testing, monitoring, and drift detection - Fine-tune Large Language Models (LLMs) and implement retrieval-augmented generation (RAG) pipelines - Build agentic workflows for reasoning, planning, and decision-making - Develop real-time and batch inference systems using Docker, Kubernetes, and Spark - Utilize state-of-the-art architectures such as transformers, diffusion models, RLHF, and multimodal pipelines - Collaborate with product and engineering teams to integrate AI models into business applications - Mentor junior team members and advocate for MLOps, scalable architecture, and responsible AI best workflows Qualifications Required: - 5+ years of experience in designing, deploying, and scaling ML/DL systems in production - Proficiency in Python and deep learning frameworks like PyTorch, TensorFlow, or JAX - Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines - Familiarity with agent-based development, including ReAct agents, function-calling, and orchestration - Strong understanding of MLOps tools such as Docker, Kubernetes, Spark, model registries, and deployment workflows - Solid software engineering background with expertise in testing, version control, and APIs - Demonstrated ability to balance innovation with scalable deployment - B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field Join AuxoAI and be part of a team that values innovation, scalability, and responsible AI practices to make a significant impact in the field of AI and machine learning.,

You will be responsible for the following key roles: - AI/ML Developer (2-3 years experience): - Develop, fine-tune, and deploy AI/ML models. - Senior AI/ML Developer (5-7 years experience): - Lead AI/ML projects, optimize large-scale models, and mentor junior developers. Qualifications required for the role include: - B.Tech / M.Tech in Computer Science, AI, or related fields. - AI/ML Developer: - 2-3 years of experience in AI/ML development, strong in Python, TensorFlow/PyTorch, data engineering. - Senior AI/ML Developer: - 5-7 years of experience with expertise in LMs, deep learning, scalable architectures, and performance optimization. - Experience with MLOps tools MLflow, Kubeflow, Docker, Kubernetes) and cloud-based AI solutions. - Strong understanding of data structures, algorithms, and model deployment. Join a team that is actively shaping the future of AI-powered applications!,

As a Tech Lead - AI at Carelon Global Solutions India, your role will involve overseeing the strategic planning, supervision, and management of AI technology initiatives within the lab environment. You will be accountable for leading a team, managing the lifecycle of ideas, and diagnosing problems to ensure successful development and implementation of innovative solutions. Additionally, you will be responsible for storytelling, document preparation, and content creation to ensure clear communication and alignment with technical language and goals. **Key Responsibilities:** - Shape the labs AI agenda aligned with emerging trends and business priorities. - Identify and evaluate AI frameworks, tools, and platforms for rapid prototyping and scaled adoption. - Collaborate with cross-functional teams to ensure AI use cases are ethically aligned, feasible, and business-relevant. - Translate business ideas into AI-powered solutions using appropriate algorithms (ML, NLP, CV, etc.). - Oversee creation and validation of datasets, models, pipelines, and AI microservices within the lab. - Ensure AI solutions are modular, interpretable, and optimized for experimentation at scale. - Own end-to-end lifecycle from ideation, model development, testing, validation, deployment, and monitoring. - Implement feedback loops for continuous learning and tuning of AI systems. - Guide AI engineers, data scientists, and junior developers on advanced AI concepts, architecture, and practices. - Build internal capability and awareness through demos, reusable components, and internal knowledge hubs. - Actively contribute to idea refinement, diagnostics, and hypothesis framing for AI applicability. - Develop explainer materials and narratives to help non-technical stakeholders understand AI outcomes. - Identify and diagnose technical problems within lab projects and solutions. - Develop and deliver compelling stories to communicate the impact and value of lab projects. - Ensure clear communication and understanding of technical language and concepts within the team and with stakeholders. - Oversee lab operations and foster an environment that supports experimentation and innovation. - Plan and manage team capacity to support diverse project needs. - Troubleshoot and resolve complex technical challenges in collaborative, agile settings. **Qualifications Required:** - Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field. - 8-10 years of experience in Technology Management. - Managed a team of 10+ Developers. - Proven experience in building and leading AI/ML initiatives and teams. - Experience with lab environments and innovation management is a plus. This role at Carelon Global Solutions India offers a world of limitless opportunities to its associates, with a focus on learning and development, innovation, creativity, holistic well-being, rewards and recognitions, health and medical insurance coverage, best-in-class amenities, and workspaces. Carelon is an equal opportunity employer that celebrates diversity and empowers its workforce to deliver the best results for customers. If you require accommodation due to a disability, you can request the Reasonable Accommodation Request Form.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Role Overview: You will engineer, ship, and operate AI powered services and APIs in production. The focus is on Python, API development, robust deployment practices, and end to end MLOps/DevOps on AWS/Azure. You'll partner with data, ML, and platform teams to move models and AI capabilities from notebooks to reliable, secure, scalable services. Key Responsibilities: - Design, build, and operate production-grade AI services/APIs, owning reliability, scalability, and performance SLOs. - Implement MLOps best practices (experiment tracking, model packaging, CI/CD for models, automated testing, feature and model registries, telemetry) to reduce time to production. - Drive DevOps automation (infrastructure as code, containerization, orchestration) and secure delivery with least privilege, secrets management, and policy-as-code. - Lead deployment of AI components to AWS/Azure (containers, serverless, managed ML platforms) with strong observability and rollback plans. - Collaborate cross-functionally to translate product and analytics requirements into well-designed APIs, contracts, and SLAs. Qualification Required: - MLOps (e.g., MLflow/Kubeflow/SageMaker/Azure ML), CI/CD for ML, model registry, monitoring - DevOps (Docker, Kubernetes, IaCTerraform/Bicep, GitHub/GitLab Actions/Azure DevOps) - Python (production code quality, testing, packaging) - Deployment to AWS/Azure (EKS/AKS, ECS/Fargate, Lambda/Functions, API Gateway/App Gateway) - API development (FastAPI/Flask, OpenAPI/Swagger, authN/Z, rate limiting, versioning) Company Details: EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

Role Overview: As a Data Scientist, your main responsibility will be to manipulate and preprocess structured and unstructured data to prepare datasets for analysis and model training. You will utilize Python libraries such as PyTorch, Pandas, and NumPy for data analysis, model development, and implementation. Additionally, you will fine-tune large language models (LLMs) to meet specific use cases and enterprise requirements. Collaboration with cross-functional teams to experiment with AI/ML models and iterate quickly on prototypes will also be a key part of your role. You will optimize workflows to ensure fast experimentation and deployment of models to production environments. Implementing containerization and basic Docker workflows to streamline deployment processes will also be part of your responsibilities. Writing clean, efficient, and production-ready Python code for scalable AI solutions will be essential. Key Responsibilities: - Manipulate and preprocess structured and unstructured data for analysis and model training. - Utilize Python libraries like PyTorch, Pandas, and NumPy for data analysis and model development. - Fine-tune large language models to meet enterprise requirements. - Collaborate with cross-functional teams to experiment with AI/ML models. - Optimize workflows for fast experimentation and deployment of models. - Implement containerization and basic Docker workflows for deployment processes. - Write clean, efficient, and production-ready Python code for scalable AI solutions. Qualifications Required: - Proficiency in Python with strong skills in libraries like PyTorch, Pandas, and NumPy. - Experience in handling both structured and unstructured datasets. - Familiarity with fine-tuning LLMs and understanding modern NLP techniques. - Basics of Docker and containerization principles. - Demonstrated ability to experiment, iterate, and deploy code rapidly in a production setting. - Strong problem-solving mindset with attention to detail. - Ability to learn and adapt quickly in a fast-paced, dynamic environment. (Note: No additional details about the company were provided in the job description),

Seeking candidate with strong math & geometry foundation, applied AI/ML experience, hands-on Python & SQL skills, creative problem-solving, plus familiarity with AWS & test-driven development.