285 Xgboost Jobs - Page 8

Company Description Webskitters Technology Solutions Pvt. Ltd. is a globally-renowned company that delivers top-notch Web and Mobile App Design, Development, Digital Marketing, Artificial Intelligence, and Internet of Things services. The company operates from offices in the USA, UK, and India, providing innovative solutions to clients worldwide. Role Description This is a full-time on-site role for a Data Science Trainer located in the Kolkata metropolitan area. The Data Science Trainer will be responsible for designing and delivering data science training programs, conducting workshops, mentoring individuals or teams, and staying updated on the latest trends and technologies in the field. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field. 1+ years of experience in a data science or analytics role (for mid-level roles). Proficiency in programming languages such as Python or R. Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, XGBoost). Strong SQL skills and familiarity with data querying languages. Excellent problem-solving skills and a strong attention to detail. Ability to translate complex data into actionable insights. Show more Show less

Job Information Date Opened 05/28/2025 Job Type Full time Industry Technology State/Province Karnataka/West Bengal Zip/Postal Code 700091/500083 City Kolkata/Bangalore Country India About Us At Innover, we endeavor to see our clients become connected, insight-driven businesses. Our integrated Digital Experiences, Data & Insights and Digital Operations studios help clients embrace digital transformation and drive unique outstanding experiences that apply to the entire customer lifecycle. Our connected studios work in tandem to reimagine the convergence of innovation, technology, people, and business agility to deliver impressive returns on investments. We help organizations capitalize on current trends and game-changing technologies molding them into future-ready enterprises. Take a look at how each of our studios represents deep pockets of expertise and delivers on the promise of data-driven, connected enterprises. Job Description About the Role Seeking a Senior Data Scientist who is equally comfortable building predictive models and architecting intelligent systems with Generative AI. This role is ideal for someone who thrives on solving complex business problems with the power of data, machine learning, and cutting-edge AI techniques — including large language models (LLMs), RAG pipelines, and prompt engineering. You’ll be at the forefront of innovation, driving the design and deployment of scalable AI solutions that power intelligent products, enhance automation, and enable smarter decision-making across the organization. Key Responsibilities Generative AI & LLMs Fine-tune and apply large language models (LLMs) for summarization, classification, generation, and dialogue use cases. Design and implement retrieval-augmented generation (RAG) pipelines using vector databases. Develop intelligent agents, agentic workflows and chat-based interfaces that translate natural language into actions or insights. Build multi-agent orchestration frameworks using tools such as LangGraph, AutoGen, or similar for enterprise-grade use cases. Create reusable prompt templates and evaluation strategies to ensure output quality and relevance. Machine Learning & Predictive Analytics Develop robust ML models for classification, regression, clustering, and time-series forecasting. Apply advanced feature engineering, model evaluation, and explainability techniques. Collaborate with stakeholders to define data-driven solutions aligned with business KPIs. Deployment & MLOps Lead the full model lifecycle from experimentation to deployment preferably using Azure, Databricks, or equivalent platforms. Monitor model performance, automate retraining, and ensure reliability through MLOps best practices. Data Strategy & Collaboration Work with data engineers to transform raw data into ML-ready datasets. Collaborate cross-functionally with product managers, developers, and business teams to turn use cases into scalable AI solutions. Mentor junior team members and contribute to AI/ML best practices across the org. Required Skills & Qualifications 4+ years of experience in data science or machine learning roles. Bachelor's, Master's degree, or Ph.D. in Computer Science, Data Science, Statistics, or a related field. Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning) Hands-on experience with Gen AI-related tech stack, including Azure cognitive search, Langchain, HuggingFace, vector DBs and agent frameworks like Autogen. Experience in fine-tuning open-source models like Llama etc. is a bonus. Strong programming skills in advanced python, with experience in SQL and cloud-based data platforms (Azure preferred). Understanding of model governance, versioning, monitoring, and evaluation. Ability to translate business problems into analytical frameworks and actionable models. Strong problem-solving mindset and ability to work in ambiguous, fast-paced environments. Strong storytelling and stakeholder communication skills.

Role & responsibilities Requires 5-8 years of proven experience in banking/payments/other domains Strong experience in developing Machine Learning models, Python & SQL Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases Detailed oriented with a proactive mindset towards problem-solving Excellent communication and presentation skills with the ability to convey complex information clearly and concisely Demonstrated ability to engage with client stake holders

Job Description: We are seeking a skilled and innovative AI/ML Engineer to design, build, and deploy machine learning solutions that solve complex business challenges in mission-critical industries. You will work with multidisciplinary teams to apply AI, ML, and deep learning techniques to large-scale datasets and real-time operational systems. Key Responsibilities: Design and implement end-to-end ML pipelines: data ingestion, model training, evaluation, and deployment Build predictive and prescriptive models using structured, unstructured, and real-time data Develop and fine-tune deep learning models for NLP, computer vision, or time series forecasting Integrate ML models into enterprise platforms, APIs, and dashboards Work closely with domain experts, data engineers, and DevOps teams to ensure production-grade performance Conduct model validation, bias testing, and post-deployment monitoring Document workflows, architecture, and results for reproducibility and audits Research and evaluate new AI tools, techniques, and trends Required Skills & Qualifications: Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or related field 5-7 years of hands-on experience in developing and deploying ML models Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost) Experience with NLP (BERT, spaCy) or CV frameworks (OpenCV, YOLO, MMDetection) Familiarity with data processing tools (Pandas, Dask, Apache Spark) Proficient in SQL and experience with time-series or sensor data Knowledge of ML Ops practices and tools (Docker, MLflow, Airflow, Kubernetes) Industry experience in Oil & Gas, Power Systems, or Urban Analytics Hands-on with edge AI (Jetson, Coral), GPU compute, and model optimization Cloud services: AWS SageMaker, Azure ML, or Google AI Platform Familiarity with REST APIs, OPC-UA integration, or SCADA data sources Knowledge of responsible AI practices (explainability, fairness, privacy).

Responsibilities Work in the capacity of Individual contributor in the project. Take lead in executing complex tasks and engage with the client to develop an understanding of needs and deliverables. Identify relevant data sources and sets to mine for client business needs. Analyze data for trends and patterns, and interpret data with a clear objective in mind. Research and devise innovative statistical/machine learning models for data analysis. Communicate analytic solutions to senior stakeholders. Candidate Profile 4– 9 years of experience in data science position (preferably in Banking and Financial Services). Master's degree in economics, mathematics, engineering, computer science, operations research or related areas is preferred; candidates with BA/BS degrees from the top tier academic institutions are also welcome to apply.Experience in programming in Python, SQL and/or SAS. Understanding of basic statistical techniques like t-tests, chi-square tests, hypothesis testing, regression analysis, etc.Excellent understanding of machine learning techniques and algorithms, such as Classification, Clustering,Random Forest, XGBoost,GBM, Neural Networks, Keras. Industry experience related to data science will be preferred over academic/online projects or courses. Good communication and presentation skills. Excellent problem-solving skills. Show more Show less

Job Summary: We are looking for a highly skilled and experienced AI/ML Developer with 3-4 years of hands-on experience to join our technology team. You will be responsible for designing, developing, and optimizing machine learning models that drive intelligent business solutions. The role involves close collaboration with cross-functional teams to deploy scalable AI systems and stay abreast of evolving trends in artificial intelligence and machine learning. Key Responsibilities: 1. Develop and Implement AI/ML Models Design, build, and implement AI/ML models tailored to solve specific business challenges, including but not limited to natural language processing (NLP), image recognition, recommendation systems, and predictive analytics. 2. Model Optimisation and Evaluation Continuously improve existing models for performance, accuracy, and scalability. 3. Data Preprocessing and Feature Engineering Collect, clean, and preprocess structured and unstructured data from various sources. Engineer relevant features to improve model performance and interpret ability. 4. Collaboration and Communication Collaborate closely with data scientists, back end engineers, product managers, and stakeholders to align model development with business goals. Communicate technical insights clearly to both technical and non-technical stakeholders. 5. Model Deployment and Monitoring Deploy models to production using MLOps practices and tools (e.g., MLflow, Docker, Kubernetes). Monitor live model performance, diagnose issues, and implement improvements as needed. 6. Staying Current with AI/ML Advancements Stay informed of current research, tools, and trends in AI and machine learning. Evaluate and recommend emerging technologies to maintain innovation within the team. 7. Code Reviews and Best Practices Participate in code reviews to ensure code quality, scalability, and adherence to best practices. Promote knowledge sharing and mentoring within the development team. Required Skills and Qualifications: Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field. 3-4 years of experience in machine learning, artificial intelligence, or applied data science roles. Strong programming skills in Python (preferred) and/or R. Proficiency in ML libraries and frameworks , including: scikit-learn, XGBoost, LightGBM, TensorFlow or Keras, PyTorch Skilled in data preprocessing and feature engineering , using; pandas, numpy, sklearn.preprocessing Practical experience in deploying ML models into production environments using REST APIs and containers. Familiarity with version control systems (e.g., Git) and containerization tools (e.g., Docker). Experience working with cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure . Understanding software development methodologies , especially Agile/Scrum. Strong analytical thinking, debugging, and problem-solving skills in real-world AI/ML applications.

Walk-in interview only -BLR No virtual Python & libraries scikit-learn, TensorFlow,PyTorch/XGBoost exp in supervised, unsupervised, and deep learning techniques Deployment tools Flask, FastAPI, Docker AWS GCP, Azure &ML,SQL Contact Maya 9880516218

We are seeking a highly skilled AI Engineer with demonstrated expertise in both traditional Machine Learning modelling and modern GenAI techniques. This role involves building scalable AI systems using foundation models, parameter- efficient fine-tuning (PEFT), and robust MLOps pipelines, while also grounding your solutions in classical machine learning principles. The ideal candidate excels at blending structured data modelling with large language model capabilities to drive intelligent, efficient, and production-ready AI systems. Key Responsibilities: Design, build, and deploy predictive systems by combining traditional ML models (e.g., regression, tree-based, time series) with Generative AI capabilities (e.g., LLMs, embeddings, GenAI-based simulation). Strong skills in prompt engineering are required to support the development and deployment of generative AI solutions. Fine-tune foundation models using PEFT techniques (e.g., LoRA, prefix tuning, adapters) for domain-specific applications. Build and maintain end-to-end MLOps pipelines for model versioning, testing, deployment, monitoring, and retraining. Use LLMs for automating feature generation, synthetic data creation, and prompt-driven scenario modelling. Manage the full AI/ML model lifecycle: experimentation, deployment, monitoring, diagnostics, and iterative enhancements. Apply and validate classical ML algorithms (e.g., XGBoost, LightGBM, ARIMA, SVMs, etc.) as benchmarks or hybrid components. Collaborate with cross-functional teams (data scientists, ML engineers, DevOps, product) to deliver AI solutions aligned with business needs. Deploy and monitor solutions in cloud environments (e.g., AWS SageMaker, GCP Vertex AI, Azure ML, REST(FAST API) with automated retraining and model health checks. Required Skills and Qualifications: Bachelors or Master’s degree in Computer Science, Machine Learning, Data Science, or related field. 3+ years of experience in AI/ML engineering, with proven success in both traditional predictive modelling and LLM-based development. Strong Python programming skills and familiarity with ML libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, and Transformers. Experience in parameter-efficient fine-tuning (PEFT) using frameworks such as Hugging Face PEFT, QLoRA, or AdapterHub. Proficiency in building MLOps workflows with tools like MLflow, Airflow, Kubeflow, or SageMaker Pipelines. Solid SQL/NoSQL experience and strong data wrangling skills. Hands-on experience deploying models in production cloud environments and containerized systems (e.g., Docker, Kubernetes). Excellent problem-solving, debugging, and communication skills.

Description We are part of the India & Emerging Stores Customer Fulfilment Experience Org. Team's mission is to address unique customer requirements and the increasing associated costs/abuse of returns and rejects for Emerging Stores. Our team implements tech solves that reduce the net cost of concessions/refunds - this includes buyer and seller abuse, costs associated with return/reject transportation, cost of contacts and operations cost at return centers. We have a huge opportunity to create a legacy and our Legacy Statement is to “transform ease and quality of living in India, thereby enabling its potential in the 21st century”. We also believe that we have an additional responsibility to “help Amazon become truly global in its perspective and innovations” by creating global best-in-class products/platforms that can serve our customers worldwide. This is an opportunity to join our mission to build tech solutions that empower sellers to delight the next billion customers. You will be responsible for building new system capabilities grounds up for strategic business initiatives. If you feel excited by the challenge of setting the course for large company wide initiatives, building and launching customer facing products in IN and other emerging markets, this may be the next big career move for you. We are building systems which can scale across multiple marketplaces and are on the state-of-the-art in automated large scale e-commerce business. We are looking for a SDE to deliver capabilities across marketplaces. We operate in a high performance agile ecosystem where SDEs, Product Managers and Principals frequently connect with end customers of our products. Our SDEs stay connected with customers through seller/FC/Deliver Station visits and customer anecdotes. This allows our engineers to significantly influence product roadmap, contribute to PRFAQs and create disproportionate impact through the tech they deliver. We offer Technology leaders a once in a lifetime opportunity to transform billions of lives across the planet through their tech innovation. As an engineer, you will help with the design, implementation, and launch of many key product features. You will get an opportunity to work on the wide range of technologies (including AWS Open Search, Lambda, ECS, SQS, Dynamo DB, Neptune etc.) and apply new technologies for solving customer problems. You will have an influence on defining product features, drive operational excellence, and spearhead the best practices that enable a quality product. You will get to work with highly skilled and motivated engineers who are already contributing to building high-scale and high-available systems. If you are looking for an opportunity to work on world-leading technologies and would like to build creative technology solutions that positively impact hundreds of millions of customers, and relish large ownership and diverse technologies, join our team today! As An Engineer You Will Be Responsible For Ownership of product/feature end-to-end for all phases from the development to the production. Ensuring the developed features are scalable and highly available with no quality concerns. Work closely with senior engineers for refining the design and implementation. Management and execution against project plans and delivery commitments. Assist directly and indirectly in the continual hiring and development of technical talent. Create and execute appropriate quality plans, project plans, test strategies and processes for development activities in concert with business and project management efforts. Contribute intellectual property through patents. The candidate should be passionate engineer about delivering experiences that delight customers and creating solutions that are robust. He/she should be able to commit and own the deliveries end-to-end. About The Team Team: IES NCRC Tech Mission: We own programs to prevent customer abuse for IN & emerging marketplaces. We detect abusive customers for known abuse patterns and apply interventions at different stages of buyer's journey like checkout, pre-fulfillment, shipment and customer contact (customer service). We closely partner with International machine learning team to build ML based solutions for above interventions. Vision: Our goal is to automate detection of new abuse patterns and act quickly to minimize financial loss to Amazon. This would act as a deterrent for abusers, while building trust for genuine customers. We use machine learning based models to automate the abuse detection in a scalable & efficient manner. Technologies: The ML models leveraged by the team include a vast variety ranging from regression-based (XgBoost), to deep-learning models (RNN, CNN) and use frameworks like PyTorch, TensorFlow, Keras for training & inference. Productionization of ML models for real-time low-latency high traffic use-cases poses unique challenges, which in turn makes the work exciting. In terms of tech stack, multiple AWS technologies are used, e.g. Sagemaker, ECS, Lambda, ElasticSearch, StepFunctions, AWS Batch, DynamoDB, S3, CDK (for infra), GraphDBs and are open to adopt new technologies as per use-case. Basic Qualifications 3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience Experience programming with at least one software programming language Preferred Qualifications 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience Bachelor's degree in computer science or equivalent Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI - Haryana Job ID: A2992237 Show more Show less

About the Role Mergen Partners is seeking a Data Scientist to join a cutting-edge AI and Data Science team. In this role, you’ll design predictive models and data-driven solutions that directly influence critical business areas such as pricing strategy, customer behavior analysis, and resource optimization. If you thrive on solving complex problems with AI and want to see your work drive tangible outcomes, this is your opportunity to make an impact. What You’ll Do Lead Analytical Strategy: Drive innovation by proposing new statistical frameworks, testing methodologies, and infrastructure enhancements to unlock business value. Collaborate Cross-Functionally: Partner with stakeholders to define challenges, develop hypotheses, and transform raw data (including conversational data) into actionable insights and scalable models. Own End-to-End Analytics: Conduct descriptive/prescriptive analyses, design experiments (A/B, multi-armed bandit), and track business metrics to inform decision-making. Build ML Solutions: Develop models to optimize customer segmentation, retention, conversation quality, and revenue growth. Mentor & Guide: Serve as the team’s AI/ML authority, overseeing advanced statistical work and model development. Ensure Model Excellence: Validate, test, and refine models for performance, scalability, and real-world applicability. What We’re Looking For Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. Experience: 2-5 years in data science, machine learning, or product analytics with hands-on model development. Technical Expertise: Proficiency in Python and SQL (BigQuery preferred). Mastery of machine learning techniques: regression, classification, clustering, time series analysis. Hands-on experience with frameworks like XGBoost, Naive Bayes, K-means, Neural Networks. Familiarity with ML libraries (TensorFlow, PyTorch, Keras). Strong grasp of statistical analysis (descriptive and inferential). Bonus Skills: Exposure to NLP, computer vision, or reinforcement learning. Experience in e-commerce, retail analytics, or product analytics. Knowledge of CI/CD pipelines for ML deployment. Familiarity with large language models (LLMs) and prompt engineering. Why Apply? Solve High-Impact Problems: Your work will shape strategies that directly affect business growth and customer experiences. Innovate with AI: Work at the forefront of AI/ML applications in a dynamic, collaborative environment. Ownership & Growth: Lead projects from ideation to deployment while mentoring peers and refining best practices. Note: Mergen Partners values diversity and is proud to support our client in building an inclusive team. All qualified applicants will receive consideration. Show more Show less

Job Title: AI/ML Developer (5 Years Experience) Location : Remote Job Type : Full-time Experience:5 Year Job Summary: We are looking for an experienced AI/ML Developer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. The ideal candidate should have strong knowledge of machine learning algorithms, data preprocessing, model evaluation, and experience with production-level ML pipelines. Key Responsibilities Model Development : Design, develop, train, and optimize machine learning and deep learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks. Data Engineering : Work with data scientists and engineers to preprocess, clean, and transform structured and unstructured datasets. ML Pipelines : Build and maintain scalable ML pipelines using tools such as MLflow, Kubeflow, Airflow, or SageMaker. Deployment : Deploy ML models into production using REST APIs, containers (Docker), or cloud services (AWS/GCP/Azure). Monitoring and Maintenance : Monitor model performance and implement retraining pipelines or drift detection techniques. Collaboration : Work cross-functionally with data scientists, software engineers, and product managers to integrate AI capabilities into applications. Research and Innovation : Stay current with the latest advancements in AI/ML and recommend new techniques or tools where applicable. Required Skills & Qualifications Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Minimum 5 years of experience in AI/ML development. Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM. Strong understanding of statistics, data structures, and ML/DL algorithms. Experience with cloud platforms (AWS/GCP/Azure) and deploying ML models in production. Experience with CI/CD tools and containerization (Docker, Kubernetes). Familiarity with SQL and NoSQL databases. Excellent problem-solving and communication skills. Preferred Qualifications Experience with NLP frameworks (e.g., Hugging Face Transformers, spaCy, NLTK). Knowledge of MLOps best practices and tools. Experience with version control systems like Git. Familiarity with big data technologies (Spark, Hadoop). Contributions to open-source AI/ML projects or publications in relevant fields. Show more Show less

Python Developer – AI Agent Development (CrewAI + LangChain) Location: Noida / Gwalior (On-site) Experience Required: Minimum 3+ years Employment Type: Full-time 🚀 About the Role We're seeking a Python Developer with hands-on experience in CrewAI and LangChain to join our cutting-edge AI product engineering team. If you thrive at the intersection of LLMs, agentic workflows, and autonomous tooling — this is your opportunity to build real-world AI agents that solve complex problems at scale. You’ll be responsible for designing, building, and deploying intelligent agents that leverage prompt engineering, memory systems, vector databases, and multi-step tool execution strategies. 🧠 Core Responsibilities Design and develop modular, asynchronous Python applications using clean code principles. Build and orchestrate intelligent agents using CrewAI: defining agents, tasks, memory, and crew dynamics. Develop custom chains and tools using LangChain (LLMChain, AgentExecutor, memory, structured tools). Implement prompt engineering techniques like ReAct, Few-Shot, and Chain-of-Thought reasoning. Integrate with APIs from OpenAI, Anthropic, HuggingFace, or Mistral for advanced LLM capabilities. Use semantic search and vector stores (FAISS, Chroma, Pinecone, etc.) to build RAG pipelines. Extend tool capabilities: web scraping, PDF/document parsing, API integrations, and file handling. Implement memory systems for persistent, contextual agent behavior. Leverage DSA and algorithmic skills to structure efficient reasoning and execution logic. Deploy containerized applications using Docker, Git, and modern Python packaging tools. 🛠️ Must-Have Skills Python 3.x (Async, OOP, Type Hinting, Modular Design) CrewAI (Agent, Task, Crew, Memory, Orchestration) – Must Have LangChain (LLMChain, Tools, AgentExecutor, Memory) Prompt Engineering (Few-Shot, ReAct, Dynamic Templates) LLMs & APIs (OpenAI, HuggingFace, Anthropic) Vector Stores (FAISS, Chroma, Pinecone, Weaviate) Retrieval-Augmented Generation (RAG) Pipelines Memory Systems: BufferMemory, ConversationBuffer, VectorStoreMemory Asynchronous Programming (asyncio, LangChain hooks) DSA / Algorithms (Graphs, Queues, Recursion, Time/Space Optimization) 💡 Bonus Skills Experience with Machine Learning libraries (Scikit-learn, XGBoost, TensorFlow basics) Familiarity with NLP concepts (Embeddings, Tokenization, Similarity scoring) DevOps familiarity (Docker, GitHub Actions, Pipenv/Poetry) 🧭 Why Join Us? Work on cutting-edge LLM agent architecture with real-world impact. Be part of a fast-paced, experiment-driven AI team. Collaborate with passionate developers and AI researchers. Opportunity to build from scratch and influence core product design. If you're passionate about building AI systems that can reason, act, and improve autonomously — we’d love to hear from you! 📩 Drop your resume and GitHub to sameer.khan@techcarrel.com. Show more Show less

In Norconsulting we are currently looking for an AI developer to join us in Chennai in a freelancer opportunity for a major Banking organization. Duration : long term Location : Chennai Rate : 110 USD/day (around 2200 USD per month) Type of assignment: Full-time (8h/day, Monday to Friday) SKILLS / EXPERIENCE REQUIRED AI Developer • Large Language Models (LLMs) & Prompt Engineering: Experience working with transformer-based models (e.g., GPT, BERT) and crafting effective prompts for tasks like summarization, text classification and document understanding. • Azure Document Intelligence: Hands-on experience with Azure AI Document Intelligence for extracting structured data from unstructured documents (invoices, forms, contracts). • Model Development & Evaluation: Strong foundation in ML algorithms, model evaluation metrics, and hyperparameter tuning using tools like Scikit-learn, XGBoost, or PyTorch. • MLOps (Machine Learning Operations): Proficient in building and managing ML pipelines using Azure ML, MLflow, and CI/CD tools for model training, deployment, and monitoring. • Azure Machine Learning (Azure ML): Experience with Azure ML Studio, automated ML, model registry, and deployment to endpoints or containers. • Azure Functions & Serverless AI: Building event-driven AI workflows using Azure Functions for real-time inference, data processing, and integration with other Azure services. • Programming Languages: Strong coding skills in Python (preferred), with knowledge of libraries like NumPy, Pandas, Scikit-learn, and Matplotlib. • Database & Data Lakes: Experience with SQL and NoSQL databases, and integration with data lakes for AI pipelines. • DevOps & Git Integration: Experience with Azure DevOps for version control, testing, and continuous integration of AI workflows. WBGJP00012309 Show more Show less

Engineer II Shape Region: India State: Karnataka City: Bangalore Description & Requirements: Who We Are? We are proud to be a growing global company with locations all around the world, from Vancouver to Shanghai, and places in between. We owe our success to our innovative product, our emphasis on our stores, our commitment to our people, and the incredible connections we get to make in every community we are in. We work together to elevate the world and we set audacious goals, nurture big growth, and engineer innovative products that allow people to feel—and perform—their best. To us, leadership is more than a role or title—it’s a way of being. About lululemon: lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative products, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people. As we continue to elevate our shopping experience, our India Tech Hub plays a key role in expanding our technology capabilities in Product Systems, Merchandising and Planning, Digital Presence, distribution and logistics, and corporate systems. Our team in India works as an extension of the global team on projects of strategic importance. About the team: The opportunity is for a role in Design & Development space in the Global Product Technology team. The objective is to align strategic intent with in-store execution and compliance to the global merchandising strategies and brand stories. We support the pre-season/in-season suite of technology solutions while living our vision to be an experiential brand and enhance the guest experience by delivering the right product, at the right place and time. We are responsible for ensuring the success of the team and proactively identify the most high-value deliverables and focus on shipping quality software solutions and other deliverables. By partnering closely with the business partners, project leads, and technical teams we help deliver project scope and ensure stakeholder expectations are met. At all levels, we demonstrate leadership by supporting the growth and development of the team as a whole and individually. At the core of our product is innovation. Planning functions are critical in understanding our guest, market, demand, and driving decisions on product placement. Our work aims to ensure end to end execution of our merchandising strategies to marry the right product to the right sizes of the boxes. Our work directly contributes to the success and growth of store planners, visual merchandising and retail teams. Who You Are? The ideal candidate performs the development of high-performing, well-tested, and thoughtfully architected software applications satisfy our internal business needs &power guest experiences; Has proven experience in effectively applying scientific, mathematical, and social principles design, build, & maintain technology products, devices, systems, and solutions that provide amazing customer experiences. A Day in the Life? Work closely with Engineers, tech lead and Solution Architects to manage the end-to-end delivery and implementation of design solutions on various tracks / projects Working on establishing best practices in the space of data engineering/ML engineering and adhering to coding practices and quality deliverables Uses algorithms, data structures, programming languages, programming paradigms to create, test, and operate sustainable client-side or server-side software applications and services. Support to Build and extend applications in the hybrid cloud and/or on-premise environments. Ensures application support is designed to be highly available, observable, and durable via software engineering best practices. Support Production issues & Prepare the system for Peak performance scaling. Works with business and systems analysts to understand end-user requirements and translate those into pragmatic & effective technical solutions. Works closely with onsite and remote frontend, backend and operations engineers to ensure deliverables are well-documented, secure, and resilient. Applies DevOps practices- brings development and IT ops processes, people, and tools closer together to increase the speed, efficiency, and quality with which we deliver technical solutions. Designs for release configuration management. Collaborates with the engineering teams (distributed globally) to deliver on integration projects. Engages in ongoing quality and performance improvement to ensure reliability and security. Mentors and leads engineers with respect to quality engineering practices, effective design principles and help them adhere to global coding standards Must Haves: Acknowledges the presence of choice in every moment and takes personal responsibility for their life. Possesses an entrepreneurial spirit and continuously innovates to achieve great results. Communicates with honesty and kindness and creates space for others to do the same. Leads with courage, knowing the possibility of greatness is bigger than the fear of failure. Fosters connection by putting people first and building trusting relationships. Integrates fun and joy as a way of being and working, aka doesn’t take themselves too seriously. Qualifications: Bachelor’s degree in computer science engineering or equivalent. 5-8+ years’ experience in Data-Engineering Tech-Stack 5-8+ years’ experience with cloud technologies AWS Python, Py-Spark as middle tier coding technology, Your proficiency in Python, SQL, and Pyspark should be impressive. Basic understand in developing and managing data pipelines, and workflows within Databricks Working experience with Big-data, PostGreSQL, ETL, Data Integration Services (Airflow, Glue, AWS services), Data Science (preferable) Experience in building data pipelines using pandas is essential for data preparation and transformation. Familiarity with Git-based tools (preferably Gitlab) ensures efficient collaboration. Experience with data warehousing solutions like Snowflake OR Redshift and familiarity with scalable storage and query optimization for large datasets. Strong software development fundamentals including design, coding, automated testing, source control, continuous integration in addition to continuous delivery and/or deployment.? Strong technical, hands-on, experience to support development, infrastructure, and operations. Knowledge of ML frameworks and libraries such as XGBoost, TensorFlow, PyTorch, and Scikit-learn for building predictive models and performing data analysis. Familiarity and understanding of DevOps – CI CD, Strong foundation on quality engineering practices. Ability to work independently with minimal direction, be a self-starter with strong initiative, and ability to manage/execute workload to deliver high quality results. Familiar with: Eclipse, Jira, Confluence, MS Office, SharePoint, Smartsheet Excellent verbal and written communication skills Support troubleshooting through solid analytical reasoning Experience in Agile methodology. Show more Show less

Quantitative Analyst: Hillroute Capital About Hillroute: Hillroute Capital is a regulated quantitative hedge fund specializing in global digital asset trading. We leverage sophisticated quantitative methodologies and advanced technology to achieve exceptional risk-adjusted returns. Our transparent approach and diverse, experienced team allow us to excel in the rapidly evolving digital asset market. About the Role: We are seeking a highly skilled Quantitative Analyst to develop, test, and refine systematic trading models across global digital asset markets. This role offers flexibility in approach—candidates with expertise in systematic strategies, options trading, statistical arbitrage, backtesting, or machine learning are equally encouraged to apply. Key Responsibilities: Strategy Development & Backtesting: Design and rigorously backtest quantitative trading models, ensuring predictive reliability and strong risk management. Quantitative & Statistical Analysis: Apply advanced statistical modeling, econometric analysis, or financial mathematics to extract market insights. Risk Management: Contribute actively to robust risk management frameworks, identifying potential risks and implementing mitigation strategies. Innovation: Regularly generate and test new ideas and strategies, pushing boundaries to enhance fund performance. Preferred Qualifications: 3–5 years experience in quantitative analysis, trading, or research roles within finance. 1-3 years experience in running quantitative machine learning models. Advanced degree in quantitative disciplines (Mathematics, Physics, Statistics, Computer Science, Engineering). Strong Python programming skills (NumPy, Pandas), and familiarity with backtesting frameworks (Backtrader, QuantConnect). Solid knowledge in options pricing, volatility modeling, statistical arbitrage, or systematic strategies. Familiarity with financial data platforms (Bloomberg, Refinitiv, Quandl). Exposure to cloud computing environments (AWS, GCP, Azure). Experience or interest in applying machine learning techniques (XGBoost, TensorFlow, PyTorch) is a plus—but not mandatory. Participation in Kaggle or similar platforms is beneficial but not required. Key Performance Indicators (KPIs): Model profitability and risk-adjusted returns. Backtest reliability and accuracy. Effectiveness in risk management. Contribution to innovation and research quality. What We Offer: Competitive compensation and performance-based incentives. The opportunity to pioneer quantitative strategies in the dynamic digital asset industry. A collaborative, inclusive, and flexible working environment. Professional growth in an innovative, fast-paced hedge fund setting. If you're passionate about quantitative finance and thrive in a dynamic, data-driven environment, we invite you to join our team. Apply directly via LinkedIn: Hillroute Capital Show more Show less

Job Requisition ID # 25WD85491 Position Overview We are looking for an experienced Principal Software Engineer to join our platform team focusing on AI/ML Platform (AMP). This team builds and maintains central components to fast track the development of new ML/AI models such as model development studio, feature store, model serving and model observability. The ideal candidate would have a background in ML Ops, Data engineering and DevOps with the experience of building high scale deployment architectures and observability. As an important contributor to our engineering team, you will help shape the future of our AI/ML capabilities, delivering solutions that inspire value for our organization. You will report directly to an Engineering Manager, and you will be based in Pune. Responsibilities System design: You will design, implement and manage software systems for the AI/ML Platform and orchestrate the full ML development lifecycle for the partner teams Mentoring: Spreading your knowledge, sharing best practices and doing design reviews to step up the expertise at the team level Multi-cloud architecture: Define components which leverages strengths from multiple cloud platforms (e.g., AWS, Azure) to optimize performance, cost, and scalability AI/ML observability: You will build systems for monitoring performance of AI/ML models and find insights on the underlying data such as drift detection, data fairness/bias and anomalies ML Solution Deployment: You will develop tools for building and deploying ML artefacts in production environments and facilitating a smooth transition from development to deployment Big Data Management: Automate and orchestrate tasks related to managing big data transformation and processing and build large-scale data stores for ML artifacts Scalable Services: Design and implement low-latency, scalable prediction, and inference services to support the diverse needs of our users Cross-Functional Collaboration: Collaborate across diverse teams, including machine learning researchers, developers, product managers, software architects, and operations, fostering a collaborative and cohesive work environment End-to-end ownership: You will take the end-to-end ownership of the components and work with other engineers in the team including design, architecture, implementation, rollout and onboarding support to partner teams, production on-call support, testing/verification, investigations etc Minimum Qualifications Educational Background: Bachelor’s degree in Computer Science or equivalent practical experience Experience: Over 8 years of experience in software development and engineering, delivering production systems and services Prior experience of working with MLOps team at the intersection of the expertise across ML model deployments, DevOps and data engineering Hands-on skills: Ability to fluently translate the design into high quality code in golang, python, Java Knowledge of DevOps practices, containerization, orchestration tools such as CI/CD, Terraform, Docker, Kubernetes, Gitops Demonstrate knowledge of distributed data processing frameworks, orchestrators, and data lake architectures using technologies such as Spark, Airflow, iceberg/ parquet formats Prior collaborations with Data science teams to deploy their models, setting up ML observability for inference level monitoring Exposure for building RAG based applications by collaborating with other product teams, Data scientists/AI engineers Demonstrate creative problem-solving skills with the ability to break down problems into manageable components Knowledge of Amazon AWS and/or Azure cloud for solutioning large scale application deployments Excellent communication and collaboration skills, fostering teamwork and effective information exchange Preferred Qualifications Experience in integrating with third party vendors Experience in latency optimization with the ability to diagnose, tune, and enhance the efficiency of serving systems Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard) Familiarity with distributed model training/inference pipelines using (KubeRay or equivalent) Exposure to leveraging GPU computing for AI/ML workloads, including experience with CUDA, OpenCL, or other GPU programming tools, to significantly enhance model training and inference performance Exposure to ML libraries such as PyTorch, TensorFlow, XGBoost, Pandas, and ScikitLearn Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers. When you’re an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us! Salary transparency Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package. Diversity & Belonging We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). Show more Show less

📢 Now Hiring: Data Science Researcher – Survey Analytics, MMM & Choice Modeling 📍 Location: Remote / Hybrid | Full-Time About the Role We're looking for a Data Science Researcher who brings statistical depth, curiosity, and a passion for real-world impact. This role is ideal for someone with a strong foundation in survey analytics , marketing mix modeling (MMM) , discrete choice modeling , and segmentation , and who wants to work at the intersection of consumer behavior and quantitative insight. If you have a Master’s in Statistics and 1+ year of hands-on experience working with consumer data, this could be the perfect place to build your career. What You’ll Be Doing 🔬 Advanced Survey & Consumer Analytics Analyze large-scale survey datasets to uncover behavioral drivers, consumer segments, and hidden insights Apply advanced statistical techniques: Latent Class Analysis , Bayesian methods , regression models, and segmentation algorithms 📊 Marketing & Choice Modeling Conduct Marketing Mix Modeling (MMM) to evaluate marketing ROI and attribution Lead Discrete Choice Modeling (DCM) projects to understand preference structures and simulate market response Translate findings into strategy-shaping insights for marketing and product teams 🛠️ Data Engineering & Experimentation Build and maintain robust data pipelines, ensuring clean integration of APIs and external data sources Merge survey data with other structured data (e.g., stock market or behavioral datasets) for multi-layered insights Run experiments to test hypotheses, forecast behavior, and optimize performance metrics 🤝 Cross-functional Collaboration Work alongside analysts, data scientists, marketers, and product teams to embed insights into decisions Present findings in clear, actionable formats for both technical and non-technical audiences Who We’re Looking For 🎓 Must-Have Master’s in Statistics (mandatory) 1+ year of experience in data analytics with a focus on survey data, MMM, DCM, or segmentation Strong hands-on skills in Python , R , SQL , and data visualization tools Familiarity with tools like Sawtooth , Bayesian networks , or XGBoost is a plus A natural storyteller with data, comfortable running experiments and finding signal in noise 🚀 Good to Have Exposure to high-frequency data (e.g., trading or behavioral datasets) Experience working with consumer research teams or market research datasets Familiarity with cloud platforms like AWS, GCP, or Azure Compensation 💰 INR 15 LPA (fixed) + performance-linked bonus 🌍 Remote-friendly, collaborative environment with high research autonomy Why This Role Stands Out You'll work on real data, real impact — from understanding why consumers choose what they do, to helping improve marketing ROI, to segmenting audiences in smarter ways. No fluff, just great problems and the freedom to solve them your way. 📨 Interested? Apply now or message us directly. Know someone perfect for this? Tag them below. Show more Show less

Job Description Job summary: Financial Institutions routinely use models for a broad range of activities including analyzing business strategies, informing business decisions, identifying and measuring risk, valuing exposures or instruments, hedging derivative positions, conducting stress testing, assessing capital adequacy, managing clients assets, informing investment process, measuring compliance with internal limits, maintaining the formal control apparatus of the bank, meeting financial or regulatory reporting requirements and issuing public disclosures. Model Risk arises from the potential adverse consequences of making decisions based on incorrect or misused model outputs and reports, leading to financial loss, poor business decision making, or reputational damage. As part of the firm’s model risk management function, Model Risk Governance and Review Group (MRGR) is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model’s appropriate usage in the business context, evaluating ongoing model performance testing, and ensuring that model users are aware of the model strengths and limitations. Model manager roles within MRGR provide attractive career paths for model development and model validation quants in a dynamic setting working closely with Model Developers, Model Users, Risk and Finance professionals, where they act as key stakeholders on day-to-day model-related risk management decisions as well as conduct independent model validation of new and existing models. Core Responsibilities The successful candidate will be a member of the MRGR Group in Bengaluru covering all Data Science across all ex-trading applications of artificial intelligence and machine learning models across CIB: Engage in new model validation activities for all Data Science models in the coverage area - evaluate conceptual soundness of model specification; reasonableness of assumptions and reliability of inputs; fit for purpose; completeness of testing performed to support the correctness of the implementation; robustness of numerical aspects; suitability and comprehensiveness of performance metrics and risk measures associated with use of model. Conduct independent testing Perform additional model review activities ranging from proposed enhancements to existing models, extensions to scope of existing models. Liaise with Model Developers, Model Users, Risk and Finance professionals to provide oversight of and guidance on appropriate usage, controls around model restrictions & limitations, and findings for ongoing performance assessment & testing Maintain model risk control apparatus of the bank for the coverage area & serve as first point of contact Keep up with the latest developments in coverage area in terms of products, markets, models, risk management practices and industry standards Essential Skills, Experience, And Qualifications A Ph.D. or Master’s degree in a Data Science oriented field such as Data Science, Computer Science or Statistics, is required. Prior experience in following backgrounds (2-4+ years): Data Science, Quantitative Model Development, Model Validation or Technology focused on Data Science including hands on experience with building/testing machine learning models Strong understanding of Machine Learning / Data Science theory, techniques and tools including Transformers, Large Language Models, NLP, GANs, Deep Learning, OCR, XGBoost, and Reinforcement Learning Understanding of the machine learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop is an asset Proficiency in Python programming. Python machine learning library and ecosystem experience: Numpy Scipy Scikit-learn Theano TensorFlow Keras PyTorch Pandas Excellent writing skills: previous experience in writing scientific text with the ability to describe evidence and present logical reasoning clearly. Strong communication skills and ability to interface with other functional areas in the bank on model-related issues Risk and control mindset: ability to ask incisive questions, converge on critical matters, assess materiality and escalate issues ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including Experience, Skills And Additional Qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical Skills Requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting. Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements: Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Experience Required - 2-5 years Skillset - Must Have Languages & Frameworks: - Python (Pandas, NumPy, Sklearn, TensorFlow, Keras, Pytorch, Tkinter, Selenium, Beautiful soup, regular expressions, Flask), R Programming, MySQL, Analytics, Data Crawling, Flask API, Statistical Modelling, Visualization. Proficient in a t least a few of the following: Regression, Bayesian methods, Tree-based learners, SVM, RF, XgBoost, Time Series Modeling, Clustering Problem-solving: Ability to break the problem into small parts and apply relevant techniques to drive required outcomes. Experience with classical ML algorithms and its underline mathematics for data patterns and profiling. Experience working with Hyper-parameter optimisation, feature engineering, feature selection, calibration of models and benchmarking performance via AUC/Gini, Capture rates, K-S and other relevant metrics Should be strong in Data Structures and Algorithms. Should be able to do code complexity analysis/optimisation. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library. Good Verbal and Written communication skills Good To Have Exposure to Production Deployment of ML models Exposure to Deep learning technologies like Computer Vision and NLP. Exposure to Cloud Technologies like AWS or Azure Cloud. Exposure to deployment tools like Docker and Kubernetes Exposure to Big Data Technologies like Hadoop, Spark, Hive etc. Responsibilities - To provide expertise on multiple phases of a ML Project/research lifecycle from design, implementation, optimisation and support. Analyse real world problems and identify AI and ML solutions Explore and visualise data to gain an understanding, and then identify differences in data distribution that could affect performance in the real world Verifying data quality, and/or ensuring it via data cleaning Find available online datasets that could be used for training Generate Synthetic data and augmentation pipelines Define validation strategies Train and retrain Models and tune their hyper parameters wherever required Fine tune pertained models via transfer learning. Design & Develop high-quality products using python, ML Libraries Show more Show less

What we're looking for: At least 5 years of experience in designing & building AI applications for customer and deploying them into production. Software engineering experience in building Secure, scalable and performant applications for customers Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI Design, develop, and operationalize existing ML models by fine tuning, personalizing it Evaluate machine learning models and perform necessary tuning Develop prompts that instruct LLM to generate relevant and accurate responses Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance Hands on customer experience with RAG solution or fine tuning of LLM model Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment Proven experience building and deploying machine learning models in production environments for real life applications Good understanding of natural language processing, computer vision or other deep learning techniques Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain) Familiarity with Google Cloud or any other Cloud Platform and its machine learning services Excellent communication, collaboration, and problem-solving skills Good to Have Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure Experience with AutoML and vision techniques Master’s degree in statistics, machine learning or related fields Show more Show less

If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere. Who We Are ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with datasolutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of theindustry and we want you to join us on our journey. ACV’s network of brands includes ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services. ACV Auctions is opening its new India Development Center in Chennai, India, and we’re looking for talented individuals to join our team. As we expand our platform, we’re offering a wide range of exciting opportunities across various roles. At ACV, we put people first and believe in the principles of trust and transparency. If you are looking for an opportunity to work with the best minds in the industry and solve unique business and technology problems? Look no further! Join us in shaping the future of the automotive marketplace! At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs. What You Will Do Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of internal stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable. The Core Responsibilities Of This Role Are Leading a team of machine learning engineers to build, automate, deploy and scale ML models and pipelines in production. Enact ML and software development best practices for the team to follow. Monitoring performance and microservice health status of models in production. Partner with external stakeholders to prioritize, scope, and deliver ML solutions Perform additional duties as assigned. What You Will Need Graduate education in a computationally intensive domain. 7+ years of prior relevant work or lab experience in ML projects/research 2+ years as tech lead or team management experience Advanced proficiency with Python and SQL (BigQuery/MySQL). Experience with building scalable REST APIs (Flask, FastAPI) Experience with building data pipelines (Airflow, Kubeflow, sklearn pipelines, etc.) Extensive knowledge of ML frameworks and libraries like Feast, XGBoost, PyTorch etc. Familiarity with cloud platforms and tools for scalable ML operations (e.g., AWS, GCP, Kubernetes). Preferred Qualifications Experience with ML model development lifecycles Prior contributions to data architecture or software architecture projects Our Values Trust & Transparency | People First | Positive Experiences | Calm Persistence | Never Settling At ACV, we are committed to an inclusive culture in which every individual is welcomed and empowered to celebrate their true selves. We achieve this by fostering a work environment of acceptance and understanding that is free from discrimination. ACV is committed to being an equal opportunity employer regardless of sex, race, creed, color, religion, marital status, national origin, age, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires reasonable accommodation, please let us know. 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 solve business problems across the organization. Most of your work will revolve around logistics and operations. What you’ll do: Design, build, and maintain predictive machine learning models and simulations to optimize solutions across Pattern. Communicate potential model improvements, data needs, and opportunities across relevant business units and developer teams. Continuously optimize the quality of our machine learning models. Conduct research to integrate new data sources, innovate in feature engineering, fine-tune algorithms, and enhance data pipelines for robust model performance. Analyze large datasets to extract actionable insights that guide business decisions. Work closely with data science teams across different regions (US and India), ensuring seamless collaboration and knowledge sharing. Follow code standards and best practices. Perform root cause analysis to determine accuracy defects and drive improvements. What we’re looking for: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Economics, or a related field. 2-6 years of industry experience in building and deploying machine learning solutions and simulations. 1-3 years of industry experience in logistics/operations. Understanding of linear programming, integer programming, and nonlinear programming Excellent communication skills (written and verbal) across departments with different levels of machine learning knowledge. 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, and deep learning models is advantageous. Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Show more Show less

Company Description Syngenta is one of the world’s leading agriculture innovation company (Part of Syngenta Group) dedicated to improving global food security by enabling millions of farmers to make better use of available resources. Through world class science and innovative crop solutions, our 60,000 people in over 100 countries are working to transform how crops are grown. We are committed to rescuing land from degradation, enhancing biodiversity and revitalizing rural communities. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. To learn more visit: www.syngenta.com Job Description Purpose Be integral part of the P&S Data Science team that applies technical expertise in data management, data science, machine learning, artificial intelligence, and automation to design, build, deploy, and maintain solutions across multiple countries. Work with project teams and SMEs to understand business requirements and develop appropriate data and AI/ML solutions. Contribute solutions with explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques to existing and new projects. Work independently to build applications for data collection and processing, exploration and visualization, analysis, regression, classification, and generation as required by the project and business teams. Accountabilities Develop and implement complex statistical models, machine learning algorithms, and data mining techniques to extract insights from large datasets. Lead data science projects from conception to completion, defining scope, methodology, and deliverables. Collaborate with business leaders to translate data insights into actionable strategies and recommendations. Guide and mentor junior data scientists, fostering their professional development and technical skills. Contribute to the design and improvement of data architecture, pipelines, and storage solutions. Stay current with the latest advancements in data science and introduce new techniques or technologies to the organization. Establish and maintain standards for data quality, documentation, and ethical use of data. Present complex findings to both technical and non-technical audiences, including executive leadership. Address complex business challenges using data-driven approaches and creative solutions. Improve the efficiency and scalability of data processing and model deployment. Develop deep knowledge in Syngenta’s P&S operations to better contextualize data insights. Own the design, build, and deploy process including collaboration with users and multi-disciplinary teams to fulfil the user, business and technical requirements. Qualifications Required Knowledge & Technical Skills Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience). Understanding of ETL processes and data pipeline design. Required development skills: Data Science – TensorFlow Scikit-learn, SciPy, NumPy, Pandas, XGBoost, Keras, etc. Programming – Python with pytorch and tensorflow Data – SQL, EDA, Descriptive and Predictive analysis, visualization Preferred additional skills: Web services – RESTful APIs and API testing, JSON, etc. Front end – JavaScript, Flask, React, Node.js, Vue, Django, or other. Tools – Git, npm, pip, Heroku, or other tools. Knowledge and hands-on experience supervised and unsupervised ML using Logistic/multi-variate regression, Gradient Boosting, Decision Trees, Neural Network, Random Forest, Support Vector Machine, Naive Bayes, Time Series, Optimization, etc. Preference for proven experience in adapting algorithms to required models - Regression, Decision Trees, Random Forests, LLM. Preference for experience in production and supply domain: production planning, supply chain, logistics, track and trace, CRM, etc. Preference for experience in Deep Learning model development in agriculture, supply chain or related domains. Documentation of documentation of APIs, models, and operational manuals (Markdown, etc.). Must be able to work on end to end activities from design, development and deployment Required Experience Previous internship, placement, or project experience in data engineering, data science, software development, or a related field. Required 2 years experience of building data science projects using AI/ML models. Exposure to cloud platforms such as AWS, Azure, Google Cloud, or Data Bricks (preferred but not essential). Additional Information Note: Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status. Follow us on: Twitter & LinkedIn https://twitter.com/SyngentaAPAC https://www.linkedin.com/company/syngenta/ India page https://www.linkedin.com/company/70489427/admin/ Show more Show less

Job Title: Consultant I/ II – Analytics Location: Ahmedabad or Gurgaon (Hybrid) Job Type: Full-Time About The Role We are looking for a Consultant I or II – Analytics to join our growing team and drive direct marketing performance through data-driven insights. In this role, you will work on end-to-end analytics tasks — from building predictive models and segmentations to uncovering actionable insights and preparing client-ready presentations. This is an exciting opportunity to make an impact on the direct marketing strategies for leading brands in the US. Key Responsibilities Build predictive models and segmentation frameworks to support marketing initiatives Target the top performing segments for the upcoming direct marketing campaigns Conduct post-campaign analysis, ad-hoc deep dives, and performance reporting Translate business problems into analytical approaches and actionable solutions Prepare clear, concise client-facing decks and present findings to business audiences Deliver high-quality, accurate, and error-free analytical outputs Skills & Qualifications 2-6 years of experience in analytics with a BE/ B.Tech or MBA/ PGDM/ MSc/ ME/ M.Tech degree Strong hands-on skills in Python/R, SAS, SQL, MS Excel, and MS PowerPoint (prior experience in SAS is preferred but not mandatory) Solid understanding and experience of machine learning techniques such as linear/logistic regression, decision trees, random forests, XGBoost, and customer segmentation Excellent communication skills with the ability to present complex technical concepts to business stakeholders Strong attention to detail, self-motivation, and a continuous learning mindset Why Join Us Be part of impactful marketing analytics projects for dynamic brands Opportunity to work in a collaborative, growth-oriented environment Flexible hybrid work setup (Ahmedabad or Gurgaon locations) Show more Show less