We are seeking a skilled Lead Software Engineer to join our team and lead a project focused on developing GenAI applications using Large Language Models (LLMs) and Python programming . In this role, you will be responsible for designing and optimizing Al-generated text prompts to maximize effectiveness for various applications. You will also collaborate with cross-functional teams to ensure seamless integration of optimized prompts into the overall product or system. Your expertise in prompt engineering principles and techniques will allow you to guide models to desired outcomes and evaluate prompt performance to identify areas for optimization and iteration. Responsibilities Design, develop, test and refine AI-generated text prompts to maximize effectiveness for various applications Ensure seamless integration of optimized prompts into the overall product or system Rigorously evaluate prompt performance using metrics and user feedback Collaborate with cross-functional teams to understand requirements and ensure prompts align with business goals and user needs Document prompt engineering processes and outcomes, educate teams on prompt best practices and keep updated on the latest AI advancements to bring innovative solutions to the project Requirements 7 to 12 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow 2-5 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English at a B2+ level for collaborating across teams, explaining technical concepts, and documenting work outcomes Show more Show less

NeuraTalk, an AI company backed by Singapore investors, is seeking a Python MLOps Engineer to join our founding team. Opportunity For Experienced candidates only. This role starts as a 3-month provisional period with a fixed pay of ₹25,000 per month. Upon successful completion, candidates will be offered a full-time role with a package of ₹6 LPA. - Annual Bonus Extra Role Overview Design, build, and maintain advanced ML Ops pipelines for cutting-edge AI models, focusing on agentic RAG, LangChain integration, fine-tuning, and scalable deployment. Open for experienced candidates passionate about ML infrastructure and automation. Technical Requirements Strong Python programming skills (Required) Experience with advanced Retrieval-Augmented Generation (RAG) systems and agentic AI design Proficiency with LangChain framework for building LLM applications Experience in fine-tuning large language models on domain-specific data Skilled in building end-to-end ML pipelines for training, validation, and deployment Familiarity with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure) Experience with CI/CD for ML models and monitoring model performance post-deployment Understanding of vector databases and embedding techniques (e.g., FAISS, Pinecone) Knowledge of model serving frameworks (e.g., FastAPI, TorchServe) Experience with experiment tracking and hyperparameter tuning tools (e.g., MLflow, Weights & Biases) Basic understanding of NLP and transformer architectures Responsibilities Develop and maintain scalable MLOps pipelines for advanced AI solutions Build and optimize agentic RAG workflows integrating LangChain and other LLM tools Fine-tune models on specialized datasets to improve accuracy and relevance Automate model deployment and monitoring to ensure high availability and performance Collaborate closely with data scientists and ML researchers to operationalize models Implement logging, alerting, and performance tracking for production models Contribute to infrastructure design for seamless model updates and rollback For Experienced Developers 2+ years in Python-based MLOps or ML Engineering roles Hands-on experience with LangChain or similar agentic AI frameworks Strong cloud deployment and container orchestration skills Proven track record of delivering production ML pipelines Ability to work independently and as part of a cross-functional team Benefits Remote work flexibility Early-stage equity (ESOP) Direct collaboration with the founding AI research and product team Opportunities for growth and leadership in AI infrastructure Future Singapore relocation opportunity Continuous learning and innovation-driven environment Work Culture Innovation-driven AI startup Remote-first with flexible working hours Transparent communication and team-oriented Direct impact on cutting-edge AI product development Equal opportunity employer promoting diversity and inclusion #AI #MLOps #Python #LangChain #RAG #MLDeployment #RemoteWork #Startup #India #Singapore Show more Show less

FairAds AI is at the forefront of revolutionizing advertising. We're seeking a highly motivated Machine Learning Engineer / Deep Learning Engineer Intern to join our pioneering team for an immediate start in Mumbai, Maharashtra, India. This is a paid, in-person position . You'll dive deep into developing and deploying, DPDP-compliant ML/DL models for real-time analytics. This is a unique opportunity to work on impactful projects involving Computer Vision, real-time data processing, and privacy-preserving AI. What You'll Help Build & Responsibilities * Develop & Implement ML/DL Models: Design, train, and fine-tune models like YOLO, DeepSORT, and DeepFace for tasks such as impression counting, dwell time analysis, and anonymized demographic analysis. * Advanced Computer Vision Tasks: Apply your OpenCV and CV knowledge for object detection, tracking, pose estimation, and image segmentation on real-world video streams. * Data Preprocessing & Management: Handle raw camera data, including cleaning, annotation, and implementing anonymization techniques (e.g., blurring, feature embeddings) to ensure DPDP Act compliance. Manage datasets using tools like DVC or cloud storage. * Edge Computing & Deployment: Optimize and deploy models on edge devices (e.g., NVIDIA Jetson, Raspberry Pi), managing real-time processing pipelines and considering power/thermal constraints. * Real-Time Analytics: Design streaming data pipelines for video feeds and optimize inference speed (e.g., using TensorRT) to deliver low-latency KPIs. * Privacy by Design: Actively contribute to building privacy-preserving ML pipelines, understanding DPDP Act principles (data minimization, consent, purpose limitation) and implementing secure data handling. * Containerization & CI/CD: Utilize Docker to package and deploy models consistently. Contribute to CI/CD pipelines for automated testing and deployment. Core Technical Skills We're Looking For * Python Programming: Proficiency in Python for ML/DL development, including libraries like PyTorch, TensorFlow, OpenCV, NumPy, Pandas, and Matplotlib. Ability to write modular, reusable code. * Machine Learning & Deep Learning: Strong understanding of supervised/unsupervised learning, neural networks (CNNs), architectures (YOLO, ResNet, ViT), transfer learning, loss functions, optimizers, and regularization. * Computer Vision: Expertise with OpenCV for image/video processing, object detection, tracking, and pose estimation. Experience handling real-time video streams. * Data Preprocessing: Skills in data cleaning, transformation, annotation, and implementing anonymization techniques. Key Domain-Specific & Deployment Skills Needed * Edge Computing: Experience or strong interest in optimizing models (pruning, quantization) for resource-constrained edge hardware (NVIDIA Jetson, Raspberry Pi) and managing real-time edge processing. * Real-Time Analytics: Ability to design streaming data pipelines and optimize for low-latency inference. * Docker & Containerization: Writing Dockerfiles and managing containers for ML model deployment. * Edge Device Deployment: Configuring edge hardware (CUDA, cuDNN), managing cross-compilation, monitoring, and potentially OTA updates. * Version Control & CI/CD (Git, GitHub Actions/Jenkins): Experience with versioning code and models (MLflow, DVC) and automation. * Cloud Integration (Optional but valued): Familiarity with AWS, Azure, or GCP for aggregating anonymized KPIs or model training. API development (Flask/FastAPI) is a plus. Soft Skills for Success * Problem-Solving & Analytical Thinking: Ability to tackle complex challenges in model performance. * Attention to Detail: Meticulous approach to data handling, model accuracy, and compliance requirements. * Pro Vibe Coder: You're someone who can skillfully navigate and debug code, especially code that might have been initially generated or assisted by AI, ensuring its robustness and efficiency. What We Offer * Pioneering Projects: Work on groundbreaking analytics solutions using advanced AI and edge computing. * Hands-on Experience: Gain invaluable experience with the full lifecycle of ML models – from conception to deployment on edge devices. * Mentorship: Learn from experienced professionals in AI, Computer Vision, and privacy-preserving technologies. * Impactful Contribution: Directly contribute to building a more intelligent and compliant ecosystem. Show more Show less

We're Hiring! Machine Learning Engineer for a B2B SaaS based startup in Noida. 🔹 Position: Machine Learning Engineer 🔹 Experience: 3.5 Years to 5 Years 🔹 Location: Noida, Sector 90 🔹 Work Mode: 5 Days | Work From Office 🔹 Notice Period: Immediate to 30 Days Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary. Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5+ years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow, and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like MLflow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills. If you’re ready to take on a leadership role and thrive in a dynamic startup environment, share your profile at gautam@mounttalent.com. Show more Show less

About Hakkoda Hakkoda, an IBM Company, is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone’s input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, India and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role Description Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic researchand industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Qualifications Education: PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Benefits Health Insurance Paid leave Technical training and certifications Robust learning and development opportunities Incentive Toastmasters Food Program Fitness Program Referral Bonus Program Hakkoda is committed to fostering diversity, equity, and inclusion within our teams. A diverse workforce enhances our ability to serve clients and enriches our culture. We encourage candidates of all races, genders, sexual orientations, abilities, and experiences to apply, creating a workplace where everyone can succeed and thrive. Ready to take your career to the next level? 🚀 💻 Apply today👇 and join a team that’s shaping the future!! Hakkoda is an IBM subsidiary which has been acquired by IBM and will be integrated in the IBM organization. Hakkoda will be the hiring entity. By Proceeding with this application, you understand that Hakkoda will share your personal information with other IBM subsidiaries involved in your recruitment process, wherever these are located. More information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here. Show more Show less

Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements. Who We Are Wayfair’s Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for an experienced Machine Learning Scientist II to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair’s revenue. What you’ll do Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support recommendations for Ads campaigns and other optimizations. Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience. Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped machine learning solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems. Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. We Are a Match Because You Have: Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, or related field. 6-9 years of industry experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale. Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Familiarity with machine learning model development frameworks, machine learning orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity Nice to have Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks). Experience in computational advertising, bidding algorithms, or search ranking Experience with deep learning frameworks like PyTorch, Tensorflow, etc. Show more Show less

Who we are Wayfair’s Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for Machine Learning Scientists to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair’s revenue. What you’ll do Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. What you’ll need 3+ years of industry experience with a Bachelor/ Master’s degree or minimum of 1-2 years of industry experience with PhD in Computer Science, Mathematics, Statistics, or related field. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Strong written and verbal communication skills Intellectual curiosity and enthusiastic about continuous learning Nice to have Experience with Python machine learning ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML) Familiarity with GCP (or AWS, Azure), machine learning model development frameworks, machine learning orchestration tools (Airflow, Kubeflow or MLFlow) Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc. Experience with deep learning frameworks like PyTorch, Tensorflow, etc. Show more Show less

Job Summary In this role, you will lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI. Job Description Company Overview: Outsourced is a leading ISO certified India & Philippines offshore outsourcing company that provides dedicated remote staff to some of the world's leading international companies. Outsourced is recognized as one of the Best Places to Work and has achieved Great Place to Work Certification. We are committed to providing a positive and supportive work environment where all staff can thrive. As an Outsourced staff member, you will enjoy a fun and friendly working environment, competitive salaries, opportunities for growth and development, work-life balance, and the chance to share your passion with a team of over 1000 talented professionals. Job Responsibilities Lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI, establishing best practices for scalability, reliability, and maintainability while actively contributing to relevant open source communities Design and develop robust, production-grade features focused on AI trustworthiness, including model monitoring Drive technical decision-making around system architecture, technology selection, and implementation strategies for key MLOps components, with a focus on open source technologies Define and implement technical standards for model deployment, monitoring, and validation pipelines, while mentoring team members on MLOps best practices and engineering excellence Collaborate with product management to translate customer requirements into technical specifications, architect solutions that address scalability and performance challenges, and provide technical leadership in customer-facing discussions Lead code reviews, architectural reviews, and technical documentation efforts to ensure high code quality and maintainable systems across distributed engineering teams Identify and resolve complex technical challenges in production environments, particularly around model serving, scaling, and reliability in enterprise Kubernetes deployments Partner with cross-functional teams to establish technical roadmaps, evaluate build-vs-buy decisions, and ensure alignment between engineering capabilities and product vision Provide technical mentorship to team members, including code review feedback, architecture guidance, and career development support while fostering a culture of engineering excellence Required Qualifications 5+ years of software engineering experience, with at least 4 years focusing on ML/AI systems in production environments Strong expertise in Python, with demonstrated experience building and deploying production ML systems Deep understanding of Kubernetes and container orchestration, particularly in ML workload contexts Extensive experience with MLOps tools and frameworks (e.g., KServe, Kubeflow, MLflow, or similar) Track record of technical leadership in open source projects, including significant contributions and community engagement Proven experience architecting and implementing large-scale distributed systems Strong background in software engineering best practices, including CI/CD, testing, and monitoring Experience mentoring engineers and driving technical decisions in a team environment Preferred Qualifications Experience with Red Hat OpenShift or similar enterprise Kubernetes platforms Contributions to ML/AI open source projects, particularly in the MLOps/GitOps space Background in implementing ML model monitoring Experience with LLM operations and deployment at scale Public speaking experience at technical conferences Advanced degree in Computer Science, Machine Learning, or related field Experience working with distributed engineering teams across multiple time zones What we Offer Health Insurance: We provide medical coverage up to 20 lakh per annum, which covers you, your spouse, and a set of parents. This is available after one month of successful engagement. Professional Development: You'll have access to a monthly upskill allowance of ₹5000 for continued education and certifications to support your career growth. Leave Policy: Vacation Leave (VL): 10 days per year, available after probation. You can carry over or encash up to 5 unused days. Casual Leave (CL): 8 days per year for personal needs or emergencies, available from day one. Sick Leave: 12 days per year, available after probation. Flexible Work Hours or Remote Work Opportunities – Depending on the role and project. Outsourced Benefits such as Paternity Leave, Maternity Leave, etc. Show more Show less

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com Job Description Blend is hiring a Senior Data Scientist (Generative AI) to spearhead the development of advanced AI-powered classification and matching systems on Databricks. You will contribute to flagship programs like the Diageo AI POC by building RAG pipelines, deploying agentic AI workflows, and scaling LLM-based solutions for high-precision entity matching and MDM modernization. Key Responsibilities Design and implement end-to-end AI pipelines for product classification, fuzzy matching, and deduplication using LLMs, RAG, and Databricks-native workflows. Develop scalable, reproducible AI solutions within Databricks notebooks and job clusters, leveraging Delta Lake, MLflow, and Unity Catalog. Engineer Retrieval-Augmented Generation (RAG) workflows using vector search and integrate with Python-based matching logic. Build agent-based automation pipelines (rule-driven + GenAI agents) for anomaly detection, compliance validation, and harmonization logic. Implement explainability, audit trails, and governance-first AI workflows aligned with enterprise-grade MDM needs. Collaborate with data engineers, BI teams, and product owners to integrate GenAI outputs into downstream systems. Contribute to modular system design and documentation for long-term scalability and maintainability. Qualifications Bachelor’s/Master’s in Computer Science, Artificial Intelligence, or related field. 5+ years of overall Data Science experience with 2+ years in Generative AI / LLM-based applications. Deep experience with Databricks ecosystem: Delta Lake, MLflow, DBFS, Databricks Jobs & Workflows. Strong Python and PySpark skills with ability to build scalable data pipelines and AI workflows in Databricks. Experience with LLMs (e.g., OpenAI, LLaMA, Mistral) and frameworks like LangChain or LlamaIndex. Working knowledge of vector databases (e.g., FAISS, Chroma) and prompt engineering for classification/retrieval. Exposure to MDM platforms (e.g., Stibo STEP) and familiarity with data harmonization challenges. Experience with explainability frameworks (e.g., SHAP, LIME) and AI audit tooling. Preferred Skills Knowledge of agentic AI architectures and multi-agent orchestration. Familiarity with Azure Data Hub and enterprise data ingestion frameworks. Understanding of data governance, lineage, and regulatory compliance in AI systems. Additional Information Thrive & Grow with Us : Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks: Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats: Dive into our casual "Growth Chats" where you can learn from the best—whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone: Stay fuelled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards: We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications: We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications. Show more Show less

Job Description: Position: Senior Technical Specialist – Data Science Location: Chennai Experience: 8+ Years Domain Expertise: AI/ML, Data Science, Cloud, DevOps, and MLOps Education: B.E. (ECE), MBA (Big Data Analytics). Job Summary: We are seeking an experienced Senior Technical Specialist - Data Science to lead AI/ML initiatives, design scalable data-driven solutions, and drive innovation. The ideal candidate will have strong expertise in AI/ML, data engineering, cloud technologies (Azure), and MLOps, with experience in managing teams and delivering AI-powered solutions for business challenges. Key Responsibilities: • Lead and mentor a team of Data Scientists to develop and deploy AI/ML models. • Architect end-to-end Machine Learning & AI solutions for complex business problems. • Design and implement Generative AI applications, including RAG-based chatbots using LLMs, LangChain, and Azure OpenAI. • Build, deploy, and monitor MLOps pipelines using MLFlow, Kubeflow, and Azure MLOps. • Develop predictive modeling, NLP applications, and deep learning frameworks using TensorFlow, PyTorch, and BERT. • Conduct data analysis and visualization using Power BI, Tableau, Matplotlib, and Streamlit. • Work with DevOps teams to automate ML workflows, optimize cloud infrastructure, and enhance model scalability. • Collaborate with business teams to define AI strategy, data-driven insights, and process improvements. • Research and implement the latest advancements in AI/ML to improve model accuracy and efficiency. Required Skills & Expertise: • Programming: Python, PowerShell, Bash, Perl • Machine Learning & Deep Learning: SVM, KNN, XGBoost, TensorFlow, PyTorch, LSTM • NLP & Generative AI: Spacy, BERT, LangChain, LlamaIndex, LLOps • Data Visualization: Tableau, Power BI, Matplotlib, Streamlit • Cloud & MLOps: Azure ML Studio, Azure OpenAI, Docker, Jenkins, GitHub, MLFlow, ClearML • Database & Big Data: MS-SQL, Data Preprocessing, Feature Engineering Preferred Qualifications: • Azure Data Scientist Certification • HackerRank Python & SQL Certification • Udacity NLP & Deep Learning Certifications Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

This role is for one of Weekday's clients Salary range: Rs 4000000 - Rs 6500000 (ie INR 40-65 LPA) Min Experience: 10 years JobType: full-time About the role As a machine learning operations leader, together with Data Science and Engineering teams, you will lead a team that creates and maintains impactful solutions for our brands across the world. From traditional machine learning to large language models, you will work and lead throughout the model lifecycle. Responsibilities: Leadership: MLOps is a team sport, and we require a leader who can elevate everyone in the MLOps organization. While technical skills and vision are required, your leadership skills will take AI and machine learning from theoretical to operational, delivering tangible value to both customers and internal teams. Pipeline Management: Architect, implement, and maintain scalable ML pipelines, with seamless integration from data ingestion to production deployment. Model Monitoring: Lead the operationalization of machine learning models, ensuring hundreds of models are continuously monitored, retrained, and optimized in real-time environments Deployment: Deploy machine learning solutions in the cloud, securely and cost effectively. Reporting: Effectively communicate actionable insights across teams using both automatic (e.g., alerts) and non-automatic methods. The type of game changing candidate we are looking for: Seasoned: Demonstrated experience of 10-15 years successfully leading teams both formally and informally. Transparent: Willingness to identify and admit errors and seek out opportunities to continually improve both in their own work and across the team. Communication: MLOps is a central node in a complex system. Clear, actionable, and concise communication, both written and verbal is a must. Coaching and Team Advancement: An MLOps leader is continually developing team members and fostering a constant flow of communication and improvement across team members. Master's/PhD degree or a strong demonstration of technical expertise in Computer Science, Machine Learning, Data Science, or a related field Multiple years of direct extensive experience with AWS Multiple years of experience with MLOps monitoring and testing tools Ability to prioritize projects effectively once clear vision and goals are identified Excited to empower DS with tools, practices, and training that simplify MLOps enough for Data Science to increasingly practice MLOps on their own and own products in production.

Youll make a difference by: Siemens is seeking a visionary and technically strong Lead AI/ML Engineer to spearhead the development of intelligent systems that power the future of sustainable and connected transportation. This role will lead the design and deployment of AI/ML solutions across domains such as efficiency improvements in software development process, predictive maintenance, traffic analytics, computer vision for rail safety, and intelligent automation in rolling stock and rail infrastructure. Key Responsibilities Lead the end-to-end lifecycle of AI/ML projectsfrom data acquisition and model development to deployment and monitoringwithin the context of mobility systems. Architect scalable ML pipelines that integrate with Siemens Mobility platforms and other edge/cloud-based systems. Collaborate with multi-functional teams including domain experts, software architects, and system engineers to translate mobility use cases into AI-driven solutions. Mentor junior engineers and data scientists, and foster a culture of innovation, quality, and continuous improvement. Evaluate and integrate innovative research in AI/ML, including generative AI, computer vision, and time-series forecasting, into real-world applications. Ensure compliance with Siemens AI ethics, cybersecurity, and data governance standards. Required Qualifications Bachelor's or Masters or PhD in Computer Science, Machine Learning, Data Science, or a related field. 7+ years of experience in AI/ML engineering, with at least 2 years in a technical leadership role. Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Proven experience deploying ML models in production, preferably in industrial or mobility environments. Familiarity with MLOps tools (e.g., MLflow, Kubeflow) and cloud platforms (Azure, AWS, or GCP). Solid understanding of data engineering, model versioning, and CI/CD for ML. Preferred Qualifications Experience in transportation, automotive, or industrial automation domains. Knowledge of edge AI deployment, sensor fusion, or real-time analytics. Contributions to open-source AI/ML projects or published research. What We Offer Opportunity to shape the future of mobility through AI innovation. Access to Siemens global network of experts, labs, and digital platforms, flexible work arrangements, and continuous learning opportunities. A mission-driven environment focused on sustainability, safety, and digital transformation. Desired Skills: 9+ years of experience is required. Great Communication skills. Analytical and problem-solving skills

Position : AI / ML Engineer Job Type : Full-Time Location : Gurgaon, Haryana, India Experience : 2 Years Industry : Information Technology Domain : Demand Forecasting in Retail/Manufacturing Job Summary We are seeking a skilled Time Series Forecasting Engineer to enhance existing Python microservices into a modular, scalable forecasting engine. The ideal candidate will have a strong statistical background, expertise in handling multi-seasonal and intermittent data, and a passion for model interpretability and real-time insights. Key Responsibilities Develop and integrate advanced time-series models: MSTL, Croston, TSB, Box-Cox. Implement rolling-origin cross-validation and hyperparameter tuning. Blend models such as ARIMA, Prophet, and XGBoost for improved accuracy. Generate SHAP-based driver insights and deliver them to a React dashboard via GraphQL. Monitor forecast performance with Prometheus and Grafana; trigger alerts based on degradation. Core Technical Skills Languages : Python (pandas, statsmodels, scikit-learn) Time Series : ARIMA, MSTL, Croston, Prophet, TSB Tools : Docker, REST API, GraphQL, Git-flow, Unit Testing Database : PostgreSQL Monitoring : Prometheus, Grafana Nice-to-Have : MLflow, ONNX, TensorFlow Probability Soft Skills Strong communication and collaboration skills Ability to explain statistical models in layman terms Proactive problem-solving attitude Comfort working cross-functionally in iterative development environments Job Type: Full-time Pay: ₹400,000.00 - ₹800,000.00 per year Application Question(s): Do you have at least 2 years of hands-on experience in Python-based time series forecasting? Have you worked in retail or manufacturing domains where demand forecasting was a core responsibility? Are you currently authorized to work in India without sponsorship? Have you implemented or used ARIMA, Prophet, or MSTL in any of your projects? Have you used Croston or TSB models for forecasting intermittent demand? Are you familiar with SHAP for model interpretability? Have you containerized a forecasting pipeline using Docker and exposed it through a REST or GraphQL API? Have you used Prometheus and Grafana to monitor model performance in production? Work Location: In person Application Deadline: 05/06/2025 Expected Start Date: 05/06/2025

Job Title: Software Engineer – AI/ML Location: Delhi Experience: 4-8 years About the Role: We are seeking a highly experienced and innovative AI & ML engineer to lead the design, development, and deployment of advanced AI/ML solutions, including Large Language Models (LLMs), for enterprise-grade applications. You will work closely with cross-functional teams to drive AI strategy, define architecture, and ensure scalable and efficient implementation of intelligent systems. Key Responsibilities: Design and architect end-to-end AI/ML solutions including data pipelines, model development, training, and deployment. Develop and implement ML models for classification, regression, NLP, computer vision, and recommendation systems. Build, fine-tune, and integrate Large Language Models (LLMs) such as GPT, BERT, LLaMA, etc., into enterprise applications. Evaluate and select appropriate frameworks, tools, and technologies for AI/ML projects. Lead AI experimentation, proof-of-concepts (PoCs), and model performance evaluations. Collaborate with data engineers, product managers, and software developers to integrate models into production environments. Ensure robust MLOps practices, version control, reproducibility, and model monitoring. Stay up to date with advancements in AI/ML, especially in generative AI and LLMs, and apply them innovatively. Requirements : Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field. Min 4+ years of experience in AI/ML. Deep understanding of machine learning algorithms, neural networks, and deep learning architectures. Proven experience working with LLMs, transformer models, and prompt engineering. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, etc. Proficiency in Python and experience with cloud platforms (AWS, Azure, or GCP) for ML workloads. Strong knowledge of MLOps tools (MLflow, Kubeflow, SageMaker, etc.) and practices. Excellent problem-solving and communication skills. Preferred Qualifications: Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and embeddings. Exposure to real-time AI systems, streaming data, or edge AI. Contributions to AI research, open-source projects, or publications in AI/ML. Interested ones, kindly apply here or share resume at hr@softprodigy.com

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are A passionate and skilled Python, AI/ML Engineers with 3-5 years of experience. You will work on cutting-edge projects involving Generative AI, machine learning, and scalable systems, helping to build intelligent solutions that deliver real business value. If you thrive in a fast-paced environment and love solving complex problems using data and intelligent algorithms, we’d love to hear from you. What You’ll Do Design, develop, and deploy machine learning models and Generative AI solutions. Work on end-to-end ML pipelines, from data ingestion and preprocessing to model deployment and monitoring. Collaborate with cross-functional teams to understand requirements and deliver AI-driven features. Build robust, scalable, and well-documented Python-based APIs for ML services. Optimize database interactions and ensure efficient data storage and retrieval for AI applications. Stay updated with the latest trends in AI/ML and integrate innovative approaches into projects. What You’ll Need Python – Strong hands-on experience. Machine Learning – Practical knowledge of supervised, unsupervised, and deep learning techniques. Generative AI – Experience working with LLMs or similar GenAI technologies. API Development – RESTful APIs and integration of ML models into production services. Databases – Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, etc.). Good To Have Cloud Platforms – Familiarity with AWS, Azure, or Google Cloud Platform (GCP). TypeScript/JavaScript – Frontend or full-stack exposure for ML product interfaces. Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, etc.) Exposure to containerization (Docker) and orchestration (Kubernetes). WHAT’S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability Show more Show less

As a Senior Machine Learning Engineer at Gojek, you will be at the forefront of applying machine learning to drive strategic and operational improvements. You will lead the development of scalable ML solutions, mentor junior engineers, and collaborate with cross-functional teams to build and deploy models that enhance our service offerings and improve operational efficiency. What You Will Do Design, develop, and deploy machine learning models to solve complex business problems and predict user behaviour. Optimise and scale real-time ML models for production environments, ensuring high availability and low latency. Architect and implement scalable and efficient ML pipelines and infrastructure. Collaborate with data scientists, engineers, and product teams to integrate ML models into production systems. Design and execute experimentation frameworks (A/B testing, multi-armed bandits, etc.) to evaluate model performance and improve decision-making. Continuously monitor and improve model performance in production, addressing concept drift, latency, and reliability challenges. Research and implement best practices in MLOps, automation, and deployment. Develop and deploy Generative AI applications, integrating LLMs and other GenAI models into production workflows. What You Will Need 4 years of hands-on experience in Machine Learning and MLOps. Proven experience in deploying and maintaining real-time machine learning models in high-traffic consumer applications. Strong understanding of system design, distributed systems, and cloud-based ML infrastructure. Proficiency in Python, TensorFlow/PyTorch, and ML frameworks. Experience with experimentation design, A/B testing, and statistical evaluation of ML models. Knowledge of feature stores, model monitoring, and automated retraining workflows. Familiarity with ML lifecycle management tools (MLflow, Kubeflow, TFX, etc.). Strong problem-solving skills and ability to work in a fast-paced environment. Our Data Science team currently consists of 40+ people based in India, Indonesia and Singapore who run Southeast Asia’s leading Gojek business. We oversee all things data and work to become a thought partner for our Business Users, Product Team, and Decision Makers. It’s our job to ensure that they have a structural approach to data-driven problem-solving. Right now, our focus revolves: how to make customers, drivers, and merchants happy and delighted. We have so far created millions of dollar impact across different journeys of customers, drivers and merchants We work with the Engineering, PMs and strategy functions hand-in-glove - be it constructing a new product or brainstorming on a problem like how do we reduce the wait time for the drive, how do we improve assortment, should we treat convenience seeking customer differently from value seeking customer etc As a team, we’re concerned not only with the growth of the company, but each other’s personal and professional growths, too. Along with us coming from diverse backgrounds, we often have fun sessions to talk about everything and anything from data information to our current movie list. About GoTo Group GoTo Group is the largest digital ecosystem in Indonesia with its mission to “Empower Progress’ by offering technological infrastructure and solutions for everyone to access and thrive in the digital economy. The GoTo ecosystem consists of on-demand transportation services, food and grocery delivery, logistics and fulfillment, as well as financial and payment services through the Gojek and GoTo Financial platforms.It is the first platform in Southeast Asia that hosts these crucial cases in a single ecosystem, capturing the majority of Indonesia’s vast consumer household. About Gojek Gojek is Southeast Asia’s leading on-demand platform and pioneer of the multi-service ecosystem with over 2.5 million driver partners across the regions offering a wide range of services such as transportation, food delivery, logistics and more. With its mission to create impact at scale, Gojek is committed to resolving consumer problems and raising standards of living by connecting consumers to the best providers of goods and services in the market. About GoTo Financial GoTo Financial accelerates financial inclusion through its leading financial services and merchants solutions. Its consumer services include GoPay and GoPayLater and serve businesses of all sizes through Midtrans, Moka, GoBiz Plus, GoBiz, and Selly. With its trusted and inclusive ecosystem of products, GoTo Financial is open to new growth opportunities and aims to empower everyone to Make It Happen, Make It Together, Make It Last. GoTo and its business units, including Gojek and GoToFinancial ("GoTo") only post job opportunities on our official channels on our respective company websites and on LinkedIn. GoTo is not liable for any job postings or job offers that did not originate from us. You should conduct your own due diligence to prevent being victims of any fake job scams, if they did not originate from GoTo's official recruitment channels. Show more Show less

Greetings from TCS!! TCS is Hiring for Data Architect Interview Mode: Virtual Required Experience: 8-18 years Work location: Chennai, Kolkata, Hyderabad Data Architect (Azure/AWS) Hands on Experience in ADF, HDInsight, Azure SQL, Pyspark, python, MS Fabric, data mesh Good to have - Spark SQL, Spark Streaming, Kafka Hands on exp in Databricks on AWS, Apache Spark, AWS S3 (Data Lake), AWS Glue, AWS Redshift / Athena Good To Have - AWS Lambda, Python, AWS CI/CD, Kafka MLflow, TensorFlow, or PyTorch, Airflow, CloudWatch If interested kindly send your updated CV and below mentioned details through E-mail: srishti.g2@tcs.com Name: E-mail ID: Contact Number: Highest qualification: Preferred Location: Highest qualification university: Current organization: Total, years of experience: Relevant years of experience: Any gap: Mention-No: of months/years (career/ education): If any then reason for gap: Is it rebegin: Previous organization name: Current CTC: Expected CTC: Notice Period: Have you worked with TCS before (Permanent / Contract ) : Show more Show less

We’re now looking for a Senior DevOps Engineer to join our fast-growing, remote-first team. If you're passionate about automation, scalable cloud systems, and supporting high-impact AI workloads, we’d love to connect. What You'll Do (Responsibilities): Design, implement, and manage scalable, secure, and high-performance cloud-native infrastructure across Azure . Build and maintain Infrastructure as Code (IaC) using Terraform or CloudFormation . Develop event-driven and serverless architectures using AWS Lambda, SQS, and SAM. Architect and manage containerized applications using Docker, Kubernetes, ECR, ECS , or AKS. Establish and optimize CI/CD pipelines using GitHub Actions, Jenkins, AWS CodeBuild & CodePipeline. Set up and manage monitoring, logging, and alerting using Prometheus + Grafana, Datadog , and centralized logging systems. Collaborate with ML Engineers and Data Engineers to support MLOps pipelines ( Airflow, ML Pipelines ) and Bedrock with Tensorflow or PyTorch . Implement and optimize ETL/data streaming pipelines using Kafka , EventBridge, and Event Hubs. Automate operations and system tasks using Python and Bash , along with Cloud CLIs and SDKs. Secure infrastructure using IAM/RBAC and follow best practices in secrets management and access control. Manage DNS and networking configurations using Cloudflare , VPC , and PrivateLink. Lead architecture implementation for scalable and secure systems, aligning with business and AI solution needs. Conduct cost optimization through budgeting, alerts, tagging, right-sizing resources, and leveraging spot instances. Contribute to backend development in Python (Web Frameworks), REST/Socket and gRPC design, and testing (unit/integration). Participate in incident response, performance tuning, and continuous system improvement. Good to Have: Hands-on experience with ML lifecycle tools like MLflow and Kubeflow Previous involvement in production-grade AI/ML projects or data-intensive systems Startup or high-growth tech company experience Qualifications: Bachelor’s degree in Computer Science, Information Technology, or a related field. 5+ years of hands-on experience in a DevOps, SRE, or Cloud Infrastructure role. Proven expertise in multi-cloud environments (AWS, Azure, GCP) and modern DevOps tooling. Strong communication and collaboration skills to work across engineering, data science, and product teams. Benefits: Competitive Salary Support for continual learning (free books and online courses) Leveling Up Opportunities Diverse team environment Show more Show less

Job Title: AI Lead Engineer Location: Vapi, Gujarat Experience Required: 5+ Years Working Days: 6 Days a Week (Monday–Saturday) Industry Exposure: Manufacturing, Retail, Finance, Healthcare, life sciences or related field. Job Description: We are seeking a highly skilled and hands-on AI Lead to join our team in Vapi . The ideal candidate will have a proven track record of developing and deploying machine learning systems in real-world environments, along with the ability to lead AI projects from concept to production. You will work closely with business and technical stakeholders to drive innovation, optimize operations, and implement intelligent automation solutions. Key Responsibilities: Lead the design, development, and deployment of AI/ML models for business-critical applications. Build and implement computer vision systems (e.g., defect detection, image recognition) using frameworks like OpenCV and YOLO. Develop predictive analytics models (e.g., predictive maintenance, forecasting) using time series and machine learning algorithms such as XGBoost. Build and deploy recommendation engines and optimization models to improve operational efficiency. Establish and maintain robust MLOps pipelines using tools such as MLflow, Docker, and Jenkins. Collaborate with stakeholders across business and IT to define KPIs and deliver AI solutions aligned with organizational objectives. Integrate AI models into existing ERP or production systems using REST APIs and microservices. Mentor and guide a team of junior ML engineers and data scientists. Required Skills & Technologies: Programming Languages: Python (advanced), SQL, Bash, Java (basic) ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost DevOps & MLOps Tools: Docker, FastAPI, MLflow, Jenkins, Git Data Engineering & Visualization: Pandas, Spark, Airflow, Tableau Cloud Platforms: AWS (S3, EC2, SageMaker – basic) Specializations: Computer Vision (YOLOv8, OpenCV), NLP (spaCy, Transformers), Time Series Analysis Deployment: ONNX, REST APIs, ERP System Integration Qualifications: B.Tech / M.Tech / M.Sc in Computer Science, Data Science, or related field. 6+ years of experience in AI/ML with a strong focus on product-ready deployments. Demonstrated experience leading AI/ML teams or projects. Strong problem-solving skills and the ability to communicate effectively with cross-functional teams. Domain experience in manufacturing, retail, or healthcare preferred. What We Offer: A leadership role in an innovation-driven team Exposure to end-to-end AI product development in a dynamic industry environment Opportunities to lead, innovate, and mentor Competitive salary and benefits package 6-day work culture supporting growth and accountability This is a startup environment but with good reputable company, We are looking for someone who can work Monday to Saturday and who can lead a team and generate new solutions and ideas and lead / manage the project effectively-- Please fill this given below form before applying https://forms.gle/8b3gdxzvc2JwnYfZ6 Show more Show less

Job Title: AI Lead Engineer Location: Vapi, Gujarat Experience Required: 5+ Years Working Days: 6 Days a Week (Monday–Saturday) Industry Exposure: Manufacturing, Retail, Finance, Healthcare, life sciences or related field. Job Description: We are seeking a highly skilled and hands-on AI Lead to join our team in Vapi . The ideal candidate will have a proven track record of developing and deploying machine learning systems in real-world environments, along with the ability to lead AI projects from concept to production. You will work closely with business and technical stakeholders to drive innovation, optimize operations, and implement intelligent automation solutions. Key Responsibilities: Lead the design, development, and deployment of AI/ML models for business-critical applications. Build and implement computer vision systems (e.g., defect detection, image recognition) using frameworks like OpenCV and YOLO. Develop predictive analytics models (e.g., predictive maintenance, forecasting) using time series and machine learning algorithms such as XGBoost. Build and deploy recommendation engines and optimization models to improve operational efficiency. Establish and maintain robust MLOps pipelines using tools such as MLflow, Docker, and Jenkins. Collaborate with stakeholders across business and IT to define KPIs and deliver AI solutions aligned with organizational objectives. Integrate AI models into existing ERP or production systems using REST APIs and microservices. Mentor and guide a team of junior ML engineers and data scientists. Required Skills & Technologies: Programming Languages: Python (advanced), SQL, Bash, Java (basic) ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost DevOps & MLOps Tools: Docker, FastAPI, MLflow, Jenkins, Git Data Engineering & Visualization: Pandas, Spark, Airflow, Tableau Cloud Platforms: AWS (S3, EC2, SageMaker – basic) Specializations: Computer Vision (YOLOv8, OpenCV), NLP (spaCy, Transformers), Time Series Analysis Deployment: ONNX, REST APIs, ERP System Integration Qualifications: B.Tech / M.Tech / M.Sc in Computer Science, Data Science, or related field. 6+ years of experience in AI/ML with a strong focus on product-ready deployments. Demonstrated experience leading AI/ML teams or projects. Strong problem-solving skills and the ability to communicate effectively with cross-functional teams. Domain experience in manufacturing, retail, or healthcare preferred. What We Offer: A leadership role in an innovation-driven team Exposure to end-to-end AI product development in a dynamic industry environment Opportunities to lead, innovate, and mentor Competitive salary and benefits package 6-day work culture supporting growth and accountability This is a startup environment but with good reputable company, We are looking for someone who can work Monday to Saturday and who can lead a team and generate new solutions and ideas and lead / manage the project effectively-- Please fill this given below form before applying https://forms.gle/8b3gdxzvc2JwnYfZ6 Show more Show less

Job Description: As a Senior Data and Applied Scientist, you will work with Pattern's Data Science team to curate and analyze data and apply machine learning models and statistical techniques to optimize advertising spend on ecommerce platforms. What you’ll do: Design, build, and maintain machine learning and statistical models to optimize advertising campaigns to improve search visibility and conversion rates on ecommerce platforms. Continuously optimize the quality of our machine learning models, especially for key metrics like search ranking, keyword bidding, CTR and conversion rate estimation Conduct research to integrate new data sources, innovate in feature engineering, fine-tuning algorithms, and enhance data pipelines for robust model performance. Analyze large datasets to extract actionable insights that guide advertising decisions. Work closely with teams across different regions (US and India), ensuring seamless collaboration and knowledge sharing. Dedicate 20% of time to MLOps for efficient, reliable model deployment and operations. What we’re looking for: Bachelor's or Master's in Data Science, Computer Science, Statistics, or a related field. 3-6 years of industry experience in building and deploying machine learning solutions. Strong data manipulation and programming skills in Python and SQL and hands-on experience with libraries such as Pandas, Numpy, Scikit-Learn, XGBoost. Strong problem-solving skills and an ability to analyze complex data. In depth expertise in a range of machine learning and statistical techniques such as linear and tree-based models along with understanding of model evaluation metrics. Experience with Git, AWS, Docker, and MLFlow is advantageous. Additional Pluses: Portfolio: An active Kaggle or Github profile showcasing relevant projects. Domain Knowledge: Familiarity with advertising and ecommerce concepts, which would help in tailoring models to business needs. Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Show more Show less

Flexera saves customers billions of dollars in wasted technology spend. A pioneer in Hybrid ITAM and FinOps, Flexera provides award-winning, data-oriented SaaS solutions for technology value optimization (TVO), enabling IT, finance, procurement and cloud teams to gain deep insights into cost optimization, compliance and risks for each business service. Flexera One solutions are built on a set of definitive customer, supplier and industry data, powered by our Technology Intelligence Platform, that enables organizations to visualize their Enterprise Technology Blueprint™ in hybrid environments—from on-premises to SaaS to containers to cloud. We’re transforming the software industry. We’re Flexera. With more than 50,000 customers across the world, we’re achieving that goal. But we know we can’t do any of that without our team. Ready to help us re-imagine the industry during a time of substantial growth and ambitious plans? Come and see why we’re consistently recognized by Gartner, Forrester and IDC as a category leader in the marketplace. Learn more at flexera.com Job Summary: We are seeking a skilled and motivated Senior Data Engineer to join our Automation, AI/ML team. In this role, you will work on designing, building, and maintaining data pipelines and infrastructure to support AI/ML initiatives, while contributing to the automation of key processes. This position requires expertise in data engineering, cloud technologies, and database systems, with a strong emphasis on scalability, performance, and innovation. Key Responsibilities: Identify and automate manual processes to improve efficiency and reduce operational overhead. Design, develop, and optimize scalable data pipelines to integrate data from multiple sources, including Oracle and SQL Server databases. Collaborate with data scientists and AI/ML engineers to ensure efficient access to high-quality data for training and inference models. Implement automation solutions for data ingestion, processing, and integration using modern tools and frameworks. Monitor, troubleshoot, and enhance data workflows to ensure performance, reliability, and scalability. Apply advanced data transformation techniques, including ETL/ELT processes, to prepare data for AI/ML use cases. Develop solutions to optimize storage and compute costs while ensuring data security and compliance. Required Skills and Qualifications: Experience in identifying, streamlining, and automating repetitive or manual processes. Proven experience as a Data Engineer, working with large-scale database systems (e.g., Oracle, SQL Server) and cloud platforms (AWS, Azure, Google Cloud). Expertise in building and maintaining data pipelines using tools like Apache Airflow, Talend, or Azure Data Factory. Strong programming skills in Python, Scala, or Java for data processing and automation tasks. Experience with data warehousing technologies such as Snowflake, Redshift, or Azure Synapse. Proficiency in SQL for data extraction, transformation, and analysis. Familiarity with tools such as Databricks, MLflow, or H2O.ai for integrating data engineering with AI/ML workflows. Experience with DevOps practices and tools, such as Jenkins, GitLab CI/CD, Docker, and Kubernetes. Knowledge of AI/ML concepts and their integration into data workflows. Strong problem-solving skills and attention to detail. Preferred Qualifications: Knowledge of security best practices, including data encryption and access control. Familiarity with big data technologies like Hadoop, Spark, or Kafka. Exposure to Databricks for data engineering and advanced analytics workflows. Flexera is proud to be an equal opportunity employer. Qualified applicants will be considered for open roles regardless of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by local/national laws, policies and/or regulations. Flexera understands the value that results from employing a diverse, equitable, and inclusive workforce. We recognize that equity necessitates acknowledging past exclusion and that inclusion requires intentional effort. Our DEI (Diversity, Equity, and Inclusion) council is the driving force behind our commitment to championing policies and practices that foster a welcoming environment for all. We encourage candidates requiring accommodations to please let us know by emailing careers@flexera.com. Show more Show less