4 Automl Jobs

Job Title : Data Scientist Location State : Tamil Nadu,Telangana Location City : Hyderabad, Chennai Experience Required : 4 to 6 Year(s) CTC Range : 7 to 11 LPA Shift: Day Shift Work Mode: Onsite Position Type: C2H Openings: 2 Company Name: VARITE INDIA PRIVATE LIMITED About The Client: Client is an Indian multinational technology company specializing in information technology services and consulting. Headquartered in Mumbai, it is a part of the Tata Group and operates in 150 locations across 46 countries. About The Job: Requirements: 5+ years in predictive analytics, with expertise in regression, classification, time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark. Familiarity with MLflow, Feature Store, and Unity Catalog for governance. Industry experience in Life Insurance or P&C. Skills: Python, PySpark , MLflow, Databricks AutoML. Predictive MoClienting (Classification , Clustering , Regression, timeseries and NLP). Cloud platform (Azure/AWS) , Delta Lake, Unity Catalog. Certifications; Databricks Certified ML Practitioner (Optional) Essential Job Functions: Design and deploy predictive models (e.g., forecasting, churn analysis, fraud detection) using Python/SQL, Spark MLlib, and Databricks ML. Build end-to-end ML pipelines (data ingestion, feature engineering, model training, deployment) on Databricks Lakehouse. Optimize model performance via hyperparameter tuning, AutoML, and MLflow tracking. Collaborate with engineering teams to operationalize models (batch/real-time) using Databricks Jobs or REST APIs. Implement Delta Lake for scalable, ACID-compliant data workflows. Enable CI/CD for ML pipelines using Databricks Repos and GitHub Actions. Troubleshoot issues in Spark Jobs and Databricks Environment. Qualifications: Skill Required: Data Science, Python for Data Science Experience Range in Required Skills: 4-6 Years How to Apply: Interested candidates are invited to submit their resume using the apply online button on this job post. About VARITE: VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services. Equal Opportunity Employer: VARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status. Unlock Rewards: Refer Candidates and Earn. If you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the referred candidate completes a three-month assignment with VARITE. Exp Req - Referral Bonus 0 - 2 Yrs. - INR 5,000 2 - 6 Yrs. - INR 7,500 6 + Yrs. - INR 10,000

Looking for an ML Engineer to design & implement AI/ML models using Python, TensorFlow, PyTorch, Scikit-learn. Optimise models, run experiments, transform data via classification/clustering, and stay updated on the latest AI/ML advancements. Required Candidate profile 3+ years of exp in AI/ML & Python Experience in TensorFlow, PyTorch, scikit-learn, Keras, AutoML, AI Clouds (H2O, AWS) Good in Data Structures, OOPS, TDD Perks and benefits Visit our Company website

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients . Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. I nviting applications for the role of AM, Data Scientist Today, the world is operating in a more dynamic market, with more capable competitors than ever before. To meet our ambitions for democratizing access to the digital economy and financial services, we need to play our very best game. That&rsquos why transforming the business to be more customer-centric and global in mindset to solve customer problems. Alongside Sales and Product functions, the Marketing function will be central to this transformation. With an ambition to create and embed a bold new operating model that will position us to compete and win in the market. It will empower marketers on the frontline and our Marketing function more broadly with the knowledge, skills, platforms, and capabilities to do exceptional work. Responsibilities Participate and collaborate with Sales and Marketing teams in the organization to understand the business requirements and to deliver scalable solutions Analyze user behavior, conversion data, customer journeys to generate hypotheses and build optimization plans and provide insights for feature improvements Mine and analyze data from company databases to drive optimization and improvement of product development and business strategies Continuously think about how to improve the analytics infrastructure for the team and automate processes Perform deep-dive analyses on key business trends from different perspectives and package the insights into easily consumable presentations and documents Provide thought leadership within the marketing analytics community Qualification we seek in you! Minimum Qualifications /skills Education in Statistics, Mathematics, Computer Science, or another quantitative field . Relevant working experience Knowledge of a variety of machine learning and Statistical techniques (Regression, Statistical Tests, Properties of distributions, Clustering, CART, SVM, etc.) and their real-world advantages/drawbacks. Experience using computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets. Experience in creating AI/ML models for Marketing use cases Experience in using industry-standard AI/ML libraries i.e. Sklearn , Keras , Tensorflow , AutoML , etc. Experience in working on Marketing Analytics Excellent communication & presentation skills Good exposure in the Marketing analytics domain for a Fintech-based client and should be able to break the problem into small chunks Ability to create models using Classification and Regression techniques and perform Hypothesis Testing and Feature selection Ability to use creativity to spot trends and tease out patterns in large datasets Good analytical and problem-solving skills, and ability to set goals and meet deadlines in a fast-paced working environment Preferred Qualification s/skills Knowledge of Hadoop/Hive is good to have Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Get to know us at www.genpact.com and on , Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.