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machine learning engineer

ai ml engineer

Oracle

<div>
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Help drive next-generation AI capabilities, with a focus on microservices, using Oracle standard tools, technology and development practices along with leading open-source frameworks
 </li>
 <li>
 Deliver high-quality software components as part of the AI Data Platform product
 </li>
 <li>
 Work with technical leads to ensure new capabilities are built with right design principles
 </li>
 <li>
 Work with remote and geographically distributed teams to operate complex cloud systems including participation in on-call rotation and related operational activities
 </li>
 <li>
 Ready to learn and jump into new areas and domains
 </li>
 </ul>
 
 
 Qualifications:
 
 
 <ul>
 <li>
 BS/MS in Computer Science or equivalent experience
 </li>
 <li>
 2-5 years of experience in Java/Python Developement
 </li>
 <li>
 Experience implementing and operating cloud services
 </li>
 <li>
 Strong proficiency in Java and related technologies. Python experience is also desired.
 </li>
 <li>
 Cloud development experience on one of the major platforms (Oracle, AWS, Azure, GCP)
 </li>
 <li>
 Solid understanding of networking concepts, security principles, and best practices.
 </li>
 <li>
 Experience with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools for managing distributed systems
 </li>
 <li>
 Familiarity with DevOps automation and tools for continuous integration, deployment, and monitoring (e.g., Terraform, Jenkins, GitLab CI/CD, Prometheus).
 </li>
 <li>
 Excellent problem-solving skills, with the ability to troubleshoot complex issues
 </li>
 <li>
 Strong communication skills, with the ability to work effectively in cross-functional teams
 </li>
 <li>
 AI/ML experience (highly desired):
 </li>
 <li>
 Experience building Generative AI, Agentic, and/or RAG systems
 </li>
 <li>
 Familiarity with latest open-source AI models/frameworks (Llama, LangGraph, etc)
 </li>
 <li>
 Understanding of ML Ops and related tooling / infrastructure
 </li>
 </ul>
</div>

Software Engineer

JPMorganChase

<div>
 
 Job Description
 
 
 
 Job Summary:
 
 
 J.P. Morgan Compliance, Conduct, and Operational Risk (CCOR) Data Science function is at the forefront of developing innovative AI and ML solutions to enhance risk management and compliance processes. Our team leverages advanced analytics, AI, Machine learning technologies, including Large Language Models (LLMs), to transform how we manage compliance, conduct, and operational risks across the organization.
 
 
 Join our CCOR Data Science team as a Lead Data Scientist, where you will play a crucial role in developing AI/ML solutions to enhance compliance and risk management. Your primary responsibilities will include leveraging advance AI / ML techniques, LLMs and Agentic AI to develop and deploy models for various tasks such as anomaly detection, risk assessment, and compliance monitoring. You will work with diverse datasets to improve our risk management processes and ensure regulatory compliance. As part of a leading analytics community, you will have opportunities for skill development and career growth in AI, machine learning, and data science.
 
 
 
 Job Responsibilities
 
 
 
 <ul>
 <li>
 Design, deploy, and manage AI/ML models, leverages advance AI/ML techniques, LLMs and Agentic AI for developing compliance and risk management related solution.
 </li>
 <li>
 Conduct research on AI techniques to enhance model performance in the compliance and risk domains.
 </li>
 <li>
 Collaborate with cross-functional teams to identify requirements, develop solutions, and deploy models in the production system.
 </li>
 <li>
 Communicate technical concepts effectively to both technical and non-technical stakeholders.
 </li>
 <li>
 Develop and maintain tools and frameworks for model training, evaluation, and optimization.
 </li>
 <li>
 Analyze and interpret data to evaluate model performance and identify areas for improvement.
 
 
 </li>
 </ul>
 
 Required Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in quantitative discipline or an MBA with an undergraduate degree in areas such as Computer Science, Statistics, Economics, Mathematics etc. from top tier Universities.
 </li>
 <li>
 Minimum of 8 years of relevant experience in developing AI/ML solutions, with recent exposure to LLMs and Agentic AI.
 </li>
 <li>
 Programming skills in Python, with experience in frameworks like PyTorch or TensorFlow.
 </li>
 <li>
 Thorough knowledge of machine learning concepts, including transformers and language modeling.
 </li>
 <li>
 Experience in data pre-processing, feature engineering, and data analysis.
 </li>
 <li>
 Excellent problem-solving skills and the ability to communicate ideas and results clearly.
 </li>
 <li>
 Familiarity with data structures and algorithms for effective problem-solving in machine learning workflows.
 
 
 </li>
 </ul>
 
 ABOUT US
 
 
 
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 About The Team
 
 
 
 Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we&rsquo;re setting our businesses, clients, customers and employees up for success.
</div>

Vice President – Data Science / Applied AI ML

HCLTech

<div>
 
 
 Job Title:
 
 
 
 
 ML Ops Engineer / ML Engineer
 
 
 
 Experience - 5Yrs -20 Yrs
 
 
 Location - Chennai / Bangalore / Hyderabad / Pune / Noida / Mumbai/
 
 
 
 
 
 
 Job Overview:
 
 
 
 We are looking for an experienced MLOps Engineer to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 Transform prototypes into production-grade models
 
 
 <ul>
 <li>
 Assist in building and maintaining machine learning pipelines and infrastructure across cloud platforms such as AWS, Azure, and GCP.
 </li>
 <li>
 Develop REST APIs or FastAPI services for model serving, enabling real-time predictions and integration with other applications.
 </li>
 <li>
 Collaborate with data scientists to design and develop drift detection and accuracy measurements for live models deployed.
 </li>
 <li>
 Collaborate with data governance and technical teams to ensure compliance with engineering standards.
 </li>
 </ul>
 
 
 Maintain models in production
 
 
 <ul>
 <li>
 Collaborate with data scientists and engineers to deploy, monitor, update, and manage models in production.
 </li>
 <li>
 Manage the full CI/CD cycle for live models, including testing and deployment.
 </li>
 <li>
 Develop logging, alerting, and mitigation strategies for handling model errors and optimize performance.
 </li>
 <li>
 Troubleshoot and resolve issues related to ML model deployment and performance.
 </li>
 <li>
 Support both batch and real-time integrations for model inference, ensuring models are accessible through APIs or scheduled batch jobs, depending on use case.
 </li>
 </ul>
 
 
 Contribute to AI platform and engineering practices
 
 
 <ul>
 <li>
 Contribute to the development and maintenance of the AI infrastructure, ensuring the models are scalable, secure, and optimized for performance.
 </li>
 <li>
 Collaborate with the team to establish best practices for model deployment, version control, monitoring, and continuous integration/continuous deployment (CI/CD).
 </li>
 <li>
 Drive the adoption of modern AI/ML engineering practices and help enhance the team&rsquo;s MLOps capabilities.
 </li>
 <li>
 Develop and maintain Flask or FastAPI-based microservices for serving models and managing model APIs.
 </li>
 </ul>
 
 
 
 
 
 Minimum Required Skills:
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, analytics, mathematics, statistics.
 </li>
 <li>
 Strong experience in Python, SQL, Pyspark.
 </li>
 <li>
 Solid understanding and knowledge of containerization technologies (Docker, Podman, Kubernetes).
 </li>
 <li>
 Proficient in CI/CD pipelines, model monitoring, and MLOps platforms (e.g., AWS SageMaker, Azure ML, MLFlow).
 </li>
 <li>
 Proficiency in cloud platforms, specifically AWS, Azure and GCP.
 </li>
 <li>
 Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
 </li>
 <li>
 Familiarity with batch processing integration for large-scale data pipelines.
 </li>
 <li>
 Experience with serving models using FastAPI, Flask, or similar frameworks for real-time inference.
 </li>
 <li>
 Certifications in AWS, Azure or ML technologies are a plus.
 </li>
 <li>
 Experience with Databricks is highly valued.
 </li>
 <li>
 Strong problem-solving and analytical skills.
 </li>
 <li>
 Ability to work in a team-oriented, collaborative environment.
 </li>
 </ul>
 
 
 
 
 
 Tools and Technologies:
 
 
 
 
 Model Development &amp; Tracking:
 
 TensorFlow, PyTorch, scikit-learn, MLflow, Weights &amp; Biases
 
 
 
 Model Packaging &amp; Serving:
 
 Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript
 
 
 
 CI/CD &amp; Pipelines:
 
 GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow
 
 
 
 Infrastructure &amp; Orchestration:
 
 Terraform, Ansible, Apache Airflow, Prefect
 
 
 
 Cloud &amp; Deployment:
 
 AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)
 
 
 
 Monitoring &amp; Logging:
 
 Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize
 
 
 
 Testing &amp; Validation:
 
 Pytest, unittest, Pydantic, Great Expectations
 
 
 
 Feature Store &amp; Data Handling:
 
 Feast, Tecton, Hopsworks, Pandas, Spark, Dask
 
 
 
 Message Brokers &amp; Data Streams:
 
 Kafka, Redis Streams
 
 
 
 Vector DB &amp; LLM Integrations (optional):
 
 Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer
 
</div>

Machine Learning Engineer

Publicis Sapient

<div>
 
 
 Role:
 
 Senior Associate &ndash; Data Science &amp; Machine Learning
 
 
 
 Experience:
 
 5 to 8 Years
 
 
 
 Work Mode:
 
 Hybrid (3 days office per week)
 
 
 
 Location:
 
 Gurugram (GGN)/Bengaluru (BEN)
 
 
 
 Notice Period:
 
 
 Immediate to 2 weeks ONLY
 
 
 
 
 Employment Type:
 
 Full-Time
 
 
 
 
 
 
 About the Role
 
 
 
 We are seeking an experienced
 
 Data Science &amp; Machine Learning Engineer
 
 who can design, build, and deploy advanced ML and AI-driven solutions. This role demands deep technical expertise in ML algorithms, deep learning architectures, LLMs, and model operationalization on cloud platforms.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Build predictive models using classification, regression, clustering, and time-series techniques.
 </li>
 <li>
 Perform feature engineering, algorithm selection, hyperparameter tuning, and model evaluation.
 </li>
 <li>
 Build
 
 deep learning models
 
 using PyTorch or TensorFlow (CNNs, RNNs, transformers).
 </li>
 <li>
 Develop
 
 GenAI applications
 
 using embeddings, LLMs, prompt engineering, RAG pipelines, LangChain, LlamaIndex, HuggingFace models.
 </li>
 <li>
 Design and implement
 
 end-to-end ML pipelines
 
 from ingestion to deployment.
 </li>
 <li>
 Build scalable data pipelines and work with cloud-based ML platforms (AWS/GCP/Azure ML).
 </li>
 <li>
 Deploy, monitor, and maintain ML models using
 
 MLOps tools
 
 and CI/CD workflows.
 </li>
 <li>
 Work closely with product and engineering teams to integrate ML solutions.
 </li>
 </ul>
 
 
 
 
 
 Must-Have Skills
 
 
 <ul>
 <li>
 Strong fundamentals:
 
 Statistics, Probability, Linear Algebra, Optimization
 
 </li>
 <li>
 Machine Learning:
 </li>
 <li>
 Classification, Regression, Clustering
 </li>
 <li>
 Model evaluation (AUC, F1, Recall, ROC curves)
 </li>
 <li>
 Cross-validation, bias-variance trade-off
 </li>
 <li>
 Deep Learning:
 </li>
 <li>
 CNNs, RNNs, Transformers
 </li>
 <li>
 Hands-on PyTorch / TensorFlow
 </li>
 <li>
 GenAI &amp; NLP:
 </li>
 <li>
 LLMs (GPT, LLaMA, Claude, etc.)
 </li>
 <li>
 Embeddings, RAG, vector databases
 </li>
 <li>
 Prompt engineering, model fine-tuning
 </li>
 <li>
 Programming:
 </li>
 <li>
 
 Python (NumPy, Pandas, Scikit-learn)
 
 </li>
 <li>
 
 PyTorch/TensorFlow
 
 </li>
 <li>
 
 SQL
 
 </li>
 <li>
 MLOps:
 </li>
 <li>
 CI/CD
 </li>
 <li>
 Model deployment &amp; monitoring
 </li>
 <li>
 Lifecycle management
 </li>
 <li>
 Version control (Git) and cloud ML platforms (AWS/GCP/Azure)
 </li>
 </ul>
 
 
 
 
 
 Good to Have
 
 
 <ul>
 <li>
 Experience with Hugging Face models
 </li>
 <li>
 Knowledge of Docker/Kubernetes
 </li>
 <li>
 Exposure to reinforcement learning
 </li>
 <li>
 Experience with A/B testing or experimentation frameworks
 </li>
 </ul>
 
 
 
 
 
 Required Candidate Information
 
 
 
 (For screening &ndash; mandatory)
 
 <ul>
 <li>
 Total Experience
 </li>
 <li>
 Relevant DS/ML Experience
 </li>
 <li>
 Current CTC
 </li>
 <li>
 Expected CTC
 </li>
 <li>
 Notice Period (
 
 Immediate &ndash; 2 weeks only
 
 )
 </li>
 <li>
 Current Location
 </li>
 <li>
 Preferred Location
 </li>
 <li>
 LinkedIn Profile URL
 </li>
 </ul>
 
 
 
 
 
 How to Apply
 
 
 
 Send your updated CV to:
 
 
 📩
 
 Vijay.S@xebia.com
 
 
</div>

Senior Associate – Data Science & Machine Learning

Weekday AI (YC W21)

<div>
 
 This role is for one of the Weekday's clients
 
 
 Salary range: Rs 600000 - Rs 800000 (ie INR 6-8 LPA)
 
 
 
 Min Experience: 0 years
 
 
 Location: Bangalore
 
 
 JobType: full-time
 
 
 We are looking for a passionate and motivated
 
 AI Engineer
 
 to join our growing team. This role is ideal for individuals who are eager to build a career in artificial intelligence and machine learning. You will work closely with data scientists, engineers, and product teams to design, develop, and deploy AI-driven solutions that power intelligent products and business applications.
 
 
 You will contribute to projects across various AI domains &mdash; including natural language processing (NLP), computer vision, recommendation systems, and predictive analytics &mdash; while continuously learning and applying state-of-the-art algorithms and tools.
 
 
 
 Requirements
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 AI Model Development: Design, implement, and train machine learning and deep learning models to solve business problems across different use cases.
 </li>
 <li>
 Data Preparation &amp; Feature Engineering: Work with large and diverse datasets to collect, clean, preprocess, and transform data for model training and evaluation.
 </li>
 <li>
 Algorithm Optimization: Experiment with different algorithms, hyperparameters, and architectures to improve model performance and efficiency.
 </li>
 <li>
 Model Deployment &amp; Integration: Collaborate with backend and DevOps teams to deploy AI models into production using frameworks like TensorFlow Serving, PyTorch, ONNX, or Docker.
 </li>
 <li>
 Research &amp; Innovation: Stay up to date with advancements in AI research and tools. Apply innovative techniques from recent papers, open-source projects, or frameworks to improve business processes.
 </li>
 <li>
 Cross-Functional Collaboration: Work with product managers and software engineers to understand business requirements and translate them into technical solutions.
 </li>
 <li>
 Performance Monitoring: Evaluate models on real-world data, monitor drift, and continuously fine-tune and retrain models to maintain accuracy and reliability.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or related field.
 </li>
 <li>
 0-3 years of hands-on experience in machine learning, AI development, or data-driven software engineering.
 </li>
 <li>
 Proficiency in programming languages such as Python (preferred) or R, with experience using libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
 </li>
 <li>
 Strong understanding of machine learning algorithms, neural networks, data preprocessing, and statistical analysis.
 </li>
 <li>
 Experience with model evaluation metrics, data visualization tools (Matplotlib, Seaborn, Power BI), and version control systems like Git.
 </li>
 <li>
 Basic understanding of cloud platforms such as AWS, GCP, or Azure, especially their AI/ML services.
 </li>
 <li>
 Familiarity with APIs, REST frameworks, and data pipelines is a plus.
 </li>
 <li>
 Excellent problem-solving ability, curiosity, and eagerness to learn emerging AI technologies.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Exposure to NLP (transformers, text classification, embeddings) or Computer Vision (CNNs, object detection).
 </li>
 <li>
 Internship or project experience involving AI/ML model deployment or end-to-end data workflows.
 </li>
 <li>
 Knowledge of MLOps tools (e.g., MLflow, Kubeflow) or containerization using Docker
 </li>
 </ul>
</div>

AI Engineer

Brillio

<div>
 
 Senior Data Specialist
 
 
 
 
 Primary Skills
 
 
 
 <ul>
 <li>
 Data Analysis, AI/ML
 
 
 </li>
 </ul>
 Job requirements
 
 
 <ul>
 <li>
 5+ years of experience in Data Science, AI, ML GenAI experience Experience in implementing AI use cases
 </li>
 </ul>
</div>

Senior Data Scientist - R01557312

Sandisk

<div>
 
 Job Description
 
 
 
 As part of the SanDisk Global IT organization, this Director-level role places you at the forefront of a company-wide transformation to embed AI into core operations and product innovation. You will play a pivotal role in executing SanDisk&rsquo;s enterprise AI strategy, with a focus on Generative AI (LLMs, agents), traditional ML, and data platform build-out.
 
 
 You will be part of a global cross-functional team driving the development of scalable AI platforms and solutions that deliver measurable business impact across manufacturing, engineering, supply chain, and other functions. Based in Bangalore, this role offers the opportunity to build and lead a high-performance team, collaborate globally, and shape the future of AI at SanDisk.
 
 
 Key Responsibilities
 
 
 Leadership &amp; Strategy
 
 
 Internalize and drive the AI/ML vision and roadmap aligned with SanDisk&rsquo;s strategic goals.
 
 
 Champion the development, adoption, and scaling of a centralized Data and AI platform supporting both GenAI and traditional ML use cases.
 
 
 Collaborate with global stakeholders across Product, Engineering, Operations, and IT to prioritize and deliver high-impact AI initiatives.
 
 
 Lead technology evaluations and drive consensus across cross-functional teams.
 
 
 Platform &amp; Architecture
 
 
 Architect and oversee the build-out of the Data and AI Platform, including:
 
 
 Lakehouse architecture
 
 
 ML lifecycle management
 
 
 GenAI capabilities (LLMs, RAG, vector databases, agentic workflows)
 
 
 Scalable cloud-native solutions (AWS, Azure, GCP)
 
 
 Drive the development of internal AI SDKs/tools to accelerate adoption across teams.
 
 
 Use Case Delivery
 
 
 Partner with Factory, Operations, and Engineering teams to identify, prioritize and implement AI use cases tied to key business KPIs such as yield improvement, predictive maintenance, and process optimization.
 
 
 Ensure responsible AI practices are embedded throughout the development and deployment lifecycle.
 
 
 Influence stakeholders and end-users to drive adoption of AI-enabled solutions.
 
 
 Team &amp; Vendor Management
 
 
 Build and mentor a world-class team of ML Engineers, Full-Stack Developers, and Data Scientists in Bangalore.
 
 
 Manage and scale vendor partnerships to augment delivery capacity and technical depth.
 
 
 
 Qualifications
 
 
 
 15-18+ Years of Professional Experience working with large Product and Services Organizations
 
 
 BS/MS in Electrical Engineering, Computer Science, Data Science
 
 
 10+ years of experience in AI/ML, with 3+ years in leadership roles managing engineering and product development teams.
 
 
 Proven track record of shipping ML/LLM systems to production in enterprise environments.
 
 
 
 Deep Expertise In
 
 
 
 Python, PyTorch/TensorFlow
 
 
 GenAI frameworks (RAG, LangChain, vector databases)
 
 
 MLOps, ML CI/CD
 
 
 Cloud platforms (AWS, Azure, GCP)
 
 
 
 Preferred
 
 
 
 Experience in the semiconductor or high-tech industry.
 
 
 Experience in use-cases with Engineering Productivity, Manufacturing Automation, Supply Chain Optimization
 
 
 Exposure to cloud-native architectures.
 
 
 Experience building internal AI platforms or SDKs used across multiple teams.
 
 
 Strong cross-functional leadership and communication skills.
 
 
 Ability to translate business goals into technical roadmaps and execution plans.
 
 
 Experience managing technology and services vendor relationships.
 
 
 
 Additional Information
 
 
 
 Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.
 
 
 Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at jobs.accommodations@sandisk.com to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
</div>

Director AIML, Enterprise Data & AI Team

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