244 Arima Jobs - Page 7

Job Summary JD- Having a background in Retail will be a Big Plus. Advanced in Python: Proven experience with core libraries like pandas, numpy, scikit-learn, and matplotlib, plus advanced tools like statsmodels, xgboost, lightgbm, prophet, deep learning-based forecasting (e.g. Neural forecast). Advanced Forecasting Techniques: Experience with ensemble models, hierarchical forecasting, probabilistic forecasting, and multivariate time series. Pricing Models: Background in price elasticity modeling, good to have experience in optimization - at least one of the 2 resources Model Evaluation: Familiarity with time-series cross-validation, backtesting, and metrics such as MAE, MAPE, RMSE, SMAPE, and prediction intervals. SQL Proficiency: Ability to query and manage data from relational databases. Version Control: Comfortable working with Git/GitHub for collaboration and code management. Mandate skill- python and advanced forcesting skills with models like arima etc. Any shift- Second shift Location-Banglore

Job Summary JD- Having a background in Retail will be a Big Plus. Advanced in Python: Proven experience with core libraries like pandas, numpy, scikit-learn, and matplotlib, plus advanced tools like statsmodels, xgboost, lightgbm, prophet, deep learning-based forecasting (e.g. Neural forecast). Advanced Forecasting Techniques: Experience with ensemble models, hierarchical forecasting, probabilistic forecasting, and multivariate time series. Pricing Models: Background in price elasticity modeling, good to have experience in optimization - at least one of the 2 resources Model Evaluation: Familiarity with time-series cross-validation, backtesting, and metrics such as MAE, MAPE, RMSE, SMAPE, and prediction intervals. SQL Proficiency: Ability to query and manage data from relational databases. Version Control: Comfortable working with Git/GitHub for collaboration and code management. Mandate skill- python and advanced forcesting skills with models like arima etc. Any shift- Second shift Location-Banglore

Senior AI/ML Engineer - R01551337 Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions • Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. • Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. • Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization • Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. • Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. • Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research • Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. • Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. • Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact • Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. • Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building • Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. • Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Years of Experience: Candidates with 4+ years of hands on experience Position: Senior Associate Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have Proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design Well versed and hands-on experience of working on optimization methods like linear programming, mixed integer programming, scheduling optimization. Having understanding of working on third party optimization solvers like Gurobi will be an added advantage Proficiency in forecasting techniques (e.g., Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats) and machine learning techniques (supervised and unsupervised) Strong command of statistical modeling, testing, and inference Proficient in using GCP tools: BigQuery, Vertex AI, Dataflow, Looker Building data pipelines and models for forecasting, optimization, and scenario planning Strong SQL and Python programming skills; experience deploying models in GCP environment Knowledge of orchestration tools like Cloud Composer (Airflow) Nice To Have Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools (e.g., Cloud composer) Strong communication and stakeholder engagement skills at the executive level Roles And Responsibilities Assist analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions Develop and execute on project & analysis plans under the guidance of Project Manager Interact with and advise consultants/clients in US as a subject matter expert to formalize data sources to be used, datasets to be acquired, data & use case clarifications that are needed to get a strong hold on data and the business problem to be solved Drive and Conduct analysis using advanced analytics tools and coach the junior team members Implement necessary quality control measures in place to ensure the deliverable integrity like data quality, model robustness, and explainability for deployments. Validate analysis outcomes, recommendations with all stakeholders including the client team Build storylines and make presentations to the client team and/or PwC project leadership team Contribute to the knowledge and firm building activities Professional And Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA from reputed institute

Senior AI/ML Engineer Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements Key Responsibilities Develop and optimize machine learning models for various applications. Implement AI algorithms, including deep learning, neural networks, and natural language processing (NLP). Design and maintain data pipelines for model training and deployment. Collaborate with cross-functional teams to integrate AI solutions into products. Conduct research on emerging AI technologies and best practices. Ensure scalability, reliability, and efficiency of AI models in production environments. Troubleshoot and improve existing AI/ML systems. Required Skills & Qualifications - Experience: 3-8 years in AI/ML development. Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and other ML frameworks. Data Handling: Strong knowledge of data preprocessing, feature engineering, and model evaluation. Cloud & Deployment: Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Problem-Solving: Ability to analyze complex problems and develop AI-driven solutions.

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

Lead AI Engineer (GenAI & AI/ML Focus) Experience : 5+ years (with at least 1-2 years in GenAI/Agentic AI) About the Role We’re seeking a Lead AI Engineer to drive the design, development, and scaling of intelligent systems powered by Generative AI and Agentic AI architectures. You’ll play a central role in shaping the technical foundation of our AI solutions, guiding junior engineers, leading experiments, and taking end-to-end ownership of core components such as prompt infrastructure, model routing logic, RAG systems, and autonomous agents. This role blends deep hands-on engineering with architectural vision and technical leadership. If you’re someone who enjoys building fast, mentoring others, and solving tough AI problems across infrastructure, experimentation, and deployment, this role is for you. What You’ll Do Architect and implement LLM-based GenAI systems: prompt pipelines, retrieval flows, model selection, fallback mechanisms, prompt optimization, prompt versioning, modular prompts, and tool orchestration strategies Design and lead multi-agent systems with memory, tool-use, task adaptation, and inter-agent collaboration using frameworks like LangGraph, CrewAI, AutoGen, LangChain Architect, deploy, and continuously evolve retrieval-augmented generation (RAG) pipelines, handle model substitution, evaluation, prompt versioning, and runtime fallback strategies Drive the creation of internal prompt libraries, LLM orchestration logic, and evaluation harnesses Collaborate on fine-tuning, embedding optimization, and multi-model substitution workflows Collaborate on model evaluation, benchmarking, and agentic stress testing in production Own end-to-end AI applications involving image, text, tabular, and signal data, working with both unimodal and multi-modal inputs Develop solutions in computer vision (e.g., OCR, classification, object detection) and multi-modal AI (e.g., text + image pipelines) Design and evaluate statistical models and classical ML systems, including time-series forecasting and predictive analytics Lead development of signal processing or anomaly detection systems (e.g., for sensor, telemetry, or log data) Build & support cost-optimization, compliance, and monitoring in GenAI deployments Mentor and unblock junior AI engineers and interns through code reviews, architecture sessions, and contribute to team knowledge base and enforce internal best practices Work closely with product, data, and platform teams to bring AI prototypes to production Partner with Data, Product, and Platform teams to ship enterprise-grade AI modules Who Should Apply You are a builder with: Minimum qualification: Bachelor’s or Master’s degree Disciplines: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or any other quantitative or computational field 5+ years of professional experience in AI/ML development (with 1-2+ years in GenAI or Agentic systems) Proven experience architecting and shipping real-world AI applications at scale Strong mentoring skills and a product-focused engineering mindset An interest in shaping the long-term AI strategy while delivering short-term wins Must-Have Skills Strong Python development skills with emphasis on modular, testable design Deep familiarity with LLM APIs, prompt frameworks (e.g., LangChain, LangGraph, CrewAI), and RAG pipelines Experience building systems for model selection, prompt fallback, tool orchestration, and versioning Familiarity with MLOps pipelines, ML monitoring, and model lifecycle management Experience in building and optimizing RAG architectures and vector database integrations Knowledge of model selection, fallbacks, prompt versioning, and task decomposition Strong grasp of autonomous agent design, reasoning, tool use, and multi-agent protocols Exposure to near real-time signal/voice processing, filtering, or event-based triggers (e.g., anomaly/event detection) Practical knowledge of statistical modeling, forecasting (ARIMA, Prophet, ML-based), or classical ML pipelines 5+ years in AI/ML engineering, including 1–2+ years working directly on GenAI/Agentic AI projects Preferred Skills Experience with multi-agent collaboration patterns (e.g., A2A, MCP) Deployment experience on GenAI platforms like OpenAI, Claude, Vertex AI, Amazon Bedrock, or Azure GenAI Familiarity with serverless deployment, egress handling, and LLM usage constraints Exposure to evaluation frameworks, benchmarking suites, or internal testing systems Experience integrating AI flows with external systems (BI tools, dashboards, APIs, automation platforms) Prior experience designing multi-modal pipelines combining vision, text, or sensor data Bonus / Good-to-Have Hands-on with fine-tuning workflows (LoRA, PEFT, etc.) Understanding of vector database internals and hybrid retrieval methods Familiarity with CV/multi-modal AI workflows using OpenCV, TorchVision, CLIP, BLIP, or related libraries Prior experience contributing to open-source GenAI libraries or leading internal tool development Why Join Us Help shape the next-gen AI stack from the ground up Work in a fast-moving environment with real ownership and autonomy Collaborate with a cross-disciplinary team at the cutting edge of GenAI and agentic systems Be part of an organization that values experimentation, modularity, and long-term impact Interested candidates can share the CV on shikha.rana@antiersolutions.com Job Type: Full-time Pay: ₹800,000.00 - ₹1,500,000.00 per year Benefits: Paid sick time Provident Fund Schedule: Day shift Monday to Friday Morning shift Application Question(s): How many days of Notice period you have? Experience: Machine learning: 4 years (Preferred) Team management: 4 years (Preferred) Location: Mohali, Punjab (Required) Work Location: In person

Licious is a fast-paced, innovative D2C brand revolutionizing the meat and seafood industry in India. We leverage cutting-edge technology, data science, and customer insights to deliver unmatched quality, convenience, and personalization. Join us to solve complex problems at scale and drive data-driven decision-making! Role Overview: We are seeking a Senior Data Scientist with 6+ years of experience to build and deploy advanced ML models (LLMs, Recommendation Systems, Demand Forecasting) and generate actionable insights. You will collaborate with cross-functional teams (Product, Supply Chain, Marketing) to optimize customer experience, demand prediction, and business growth. Key Responsibilities: 1. Machine Learning & AI Solutions: Develop and deploy Large Language Models (LLMs) for customer support automation, personalized content generation, and sentiment analysis. Enhance Recommendation Systems (collaborative filtering, NLP-based, reinforcement learning) to drive engagement and conversions. Build scalable Demand Forecasting models (time series, causal inference) to optimize inventory and supply chain. 2. Data-Driven Insights: Analyze customer behavior, transactional data, and market trends to uncover growth opportunities. Create dashboards and reports (using Tableau/Power BI) to communicate insights to stakeholders. 3. Cross-Functional Collaboration: Partner with Engineering to productionize models (MLOps, APIs, A/B testing). Work with Marketing to design hyper-personalized campaigns using CLV, churn prediction, and segmentation. 4. Innovation & Scalability: Stay updated with advancements in GenAI, causal ML, and optimization techniques. Improve model performance through feature engineering, ensemble methods, and experimentation. Qualifications: Education: BTech/MTech/MS/Ph.D. in Computer Science, Statistics, or related fields. Experience: 6+ years in Data Science, with hands-on expertise in: LLMs (GPT, BERT, fine-tuning, prompt engineering). Recommendation Systems (matrix factorization, neural CF, graph-based). Demand Forecasting (ARIMA, Prophet, LSTM, Bayesian methods). Python/R , SQL, PySpark, and ML frameworks (TensorFlow, PyTorch, scikit-learn). Cloud platforms (AWS/GCP) and MLOps tools (MLflow, Kubeflow).

Lead AI Engineer (GenAI & AI/ML Focus) Experience : 5+ years (with at least 1-2 years in GenAI/Agentic AI) About the Role We’re seeking a Lead AI Engineer to drive the design, development, and scaling of intelligent systems powered by Generative AI and Agentic AI architectures. You’ll play a central role in shaping the technical foundation of our AI solutions, guiding junior engineers, leading experiments, and taking end-to-end ownership of core components such as prompt infrastructure, model routing logic, RAG systems, and autonomous agents. This role blends deep hands-on engineering with architectural vision and technical leadership. If you’re someone who enjoys building fast, mentoring others, and solving tough AI problems across infrastructure, experimentation, and deployment, this role is for you. What You’ll Do Architect and implement LLM-based GenAI systems: prompt pipelines, retrieval flows, model selection, fallback mechanisms, prompt optimization, prompt versioning, modular prompts, and tool orchestration strategies Design and lead multi-agent systems with memory, tool-use, task adaptation, and inter-agent collaboration using frameworks like LangGraph, CrewAI, AutoGen, LangChain Architect, deploy, and continuously evolve retrieval-augmented generation (RAG) pipelines, handle model substitution, evaluation, prompt versioning, and runtime fallback strategies Drive the creation of internal prompt libraries, LLM orchestration logic, and evaluation harnesses Collaborate on fine-tuning, embedding optimization, and multi-model substitution workflows Collaborate on model evaluation, benchmarking, and agentic stress testing in production Own end-to-end AI applications involving image, text, tabular, and signal data, working with both unimodal and multi-modal inputs Develop solutions in computer vision (e.g., OCR, classification, object detection) and multi-modal AI (e.g., text + image pipelines) Design and evaluate statistical models and classical ML systems, including time-series forecasting and predictive analytics Lead development of signal processing or anomaly detection systems (e.g., for sensor, telemetry, or log data) Build & support cost-optimization, compliance, and monitoring in GenAI deployments Mentor and unblock junior AI engineers and interns through code reviews, architecture sessions, and contribute to team knowledge base and enforce internal best practices Work closely with product, data, and platform teams to bring AI prototypes to production Partner with Data, Product, and Platform teams to ship enterprise-grade AI modules Who Should Apply You are a builder with: Minimum qualification: Bachelor’s or Master’s degree Disciplines: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or any other quantitative or computational field 5+ years of professional experience in AI/ML development (with 1-2+ years in GenAI or Agentic systems) Proven experience architecting and shipping real-world AI applications at scale Strong mentoring skills and a product-focused engineering mindset An interest in shaping the long-term AI strategy while delivering short-term wins Must-Have Skills Strong Python development skills with emphasis on modular, testable design Deep familiarity with LLM APIs, prompt frameworks (e.g., LangChain, LangGraph, CrewAI), and RAG pipelines Experience building systems for model selection, prompt fallback, tool orchestration, and versioning Familiarity with MLOps pipelines, ML monitoring, and model lifecycle management Experience in building and optimizing RAG architectures and vector database integrations Knowledge of model selection, fallbacks, prompt versioning, and task decomposition Strong grasp of autonomous agent design, reasoning, tool use, and multi-agent protocols Exposure to near real-time signal/voice processing, filtering, or event-based triggers (e.g., anomaly/event detection) Practical knowledge of statistical modeling, forecasting (ARIMA, Prophet, ML-based), or classical ML pipelines 5+ years in AI/ML engineering, including 1–2+ years working directly on GenAI/Agentic AI projects Preferred Skills Experience with multi-agent collaboration patterns (e.g., A2A, MCP) Deployment experience on GenAI platforms like OpenAI, Claude, Vertex AI, Amazon Bedrock, or Azure GenAI Familiarity with serverless deployment, egress handling, and LLM usage constraints Exposure to evaluation frameworks, benchmarking suites, or internal testing systems Experience integrating AI flows with external systems (BI tools, dashboards, APIs, automation platforms) Prior experience designing multi-modal pipelines combining vision, text, or sensor data Bonus / Good-to-Have Hands-on with fine-tuning workflows (LoRA, PEFT, etc.) Understanding of vector database internals and hybrid retrieval methods Familiarity with CV/multi-modal AI workflows using OpenCV, TorchVision, CLIP, BLIP, or related libraries Prior experience contributing to open-source GenAI libraries or leading internal tool development Why Join Us Help shape the next-gen AI stack from the ground up Work in a fast-moving environment with real ownership and autonomy Collaborate with a cross-disciplinary team at the cutting edge of GenAI and agentic systems Be part of an organization that values experimentation, modularity, and long-term impact Interested candidates can share the CV on shikha.rana@antiersolutions.com Job Type: Full-time Pay: ₹800,000.00 - ₹1,500,000.00 per year Benefits: Paid sick time Provident Fund Schedule: Day shift Monday to Friday Morning shift Application Question(s): How many days of Notice period you have? Experience: Machine learning: 4 years (Preferred) Team management: 4 years (Preferred) Location: Mohali, Punjab (Required) Work Location: In person

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 the Content team. Our team is fast-paced and taking on exciting new initiatives to support a fast-growing business. We strive to adopt leading-edge technology and seek to continuously improve on the solutions we have. We are not afraid to try new things, have fun, and encourage each other to take on new challenges. We support each other in growing professionally and personally. We fail forward and learn from our mistakes, thus creating a better path ahead. We create space for team members to share feedback and ideas that can help us continually grow as an organization. We operate in agile methodology and contribute to product teams across our various functions as well as a core commerce platform team. We institute a culture of fun and lightheartedness to enjoy work each day. We are inclusive and know that we are stronger as a team than as an individual. Responsibilities: Develop Statistical/Machine Learning models / analysis for Merchandising and Planning Business problems Play a key role in all stages of the Data science project life cycle Collaborate with Product Management, Business teams to gain Business understanding, Collect requirements Identify data sources required, automate collection process Perform pre-processing, exploratory data analysis Evaluation / Interpretation of results and presentation to Stakeholders, Business leaders Collaborate with engineering and product development teams for deploying models into production systems, when applicable Requirements and skills: Proven experience in technical delivery of solutions with Time Series / Machine Learning techniques Strong applied Statistical skills, including knowledge of Statistical tests, distributions etc. Strong applied Machine Learning skills (Time Series, Regression Analysis, Supervised and Unsupervised Learning) Strong Programming Skills in Python and database query languages like SQL . Familiarity with Snowflake & Databricks is an added advantage Experience with time series forecasting techniques such ARIMA, Prophet, Deep AR Experience with data visualization libraries like Plotly, Business intelligence tools (e.g. PowerBI, Tableau) Excellent communication and presentation skills Experience in Retail industry Responsibilities: Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Job Title: Advanced Machine Learning Tutor Location: Fully Remote Type: Part-Time (Weekend Only) Salary: ₹40,000 – ₹50,000 per month Role Overview We are seeking a skilled and passionate Advanced Machine Learning Tutor to teach learners who have already completed foundational ML topics. You will conduct remote weekend classes , mentor students through hands-on projects, and explain the real-world use of advanced algorithms and techniques. This role is perfect for ML professionals who love teaching, enjoy simplifying complex ideas, and want to make a real impact on career-oriented learners. Key Responsibilities Deliver live weekend sessions on advanced ML concepts, such as: Ensemble Methods (Bagging, Boosting, Stacking) Feature Engineering and Selection Techniques Model Evaluation & Validation (Cross-Validation, ROC-AUC, etc.) Unsupervised Learning (PCA, Clustering techniques like K-Means, DBSCAN) Time Series Forecasting (ARIMA, Prophet, LSTM basics) Hyperparameter Tuning (GridSearchCV, RandomizedSearch, Bayesian Optimization) Introduction to Deep Learning (optional, depending on scope) Guide students through project-based learning using real-world datasets. Support students with doubts, debugging, and tool usage (like scikit-learn, XGBoost, LightGBM). Collaborate on curriculum refinement and improve content delivery. Keep updated with current trends in ML and bring them into your teaching. Required Qualifications Strong experience in Machine Learning beyond basic models Proficient with Python, NumPy, pandas, scikit-learn, XGBoost, etc. Familiar with advanced concepts like model selection, bias-variance tradeoff, overfitting/underfitting solutions Ability to explain and mentor real-world ML projects Previous teaching, tutoring, or mentoring experience (preferred) Excellent communication and presentation skills Nice to Have Familiarity with MLOps basics and tools (like MLflow) Experience with real-time or production ML systems Exposure to research papers or Kaggle competitions Understanding of Time Series and basic DL models like LSTMs Prior educational or ed-tech experience Students Will Learn To: Build and fine-tune complex ML models Evaluate model performance using advanced techniques Work with imbalanced datasets and noise Engineer features for better accuracy Solve real-world problems (credit risk, fraud detection, forecasting, etc.)

Job Description: We are seeking a skilled AI Engineer with 2-4 years of experience to design, develop, and deploy AI/ML solutions, with a strong emphasis on Generative AI, NLP, Retrieval-Augmented Generation (RAG), and Time Series Forecasting. The ideal candidate will have hands-on experience with LangGraph and other Generative AI frameworks to build cutting-edge AI applications. Key Responsibilities Develop and deploy AI/ML models with a focus on NLP, Generative AI, RAG, and Time Series Forecasting workflows. Engineer and refine prompts to optimize performance for large language models (LLMs) and generative AI applications. Implement and maintain data preprocessing pipelines, including data cleansing, feature engineering, embedding generation, and transformation for time series data. Develop end-to-end solutions integrating LLMs with VectorDB (e.g., Weaviate, Pinecone, FAISS) for document retrieval, semantic search, and contextual query answering. Utilize LangGraph and other Generative AI frameworks to build structured workflows for LLM-based applications. Train and fine-tune machine learning models, including LLMs, to optimize performance for various use cases. Analyze and interpret complex datasets, including time series data, ensuring scalable and efficient AI model deployment. Collaborate with cross-functional teams to integrate AI/ML models into existing systems and workflows. Ensure models are robust, scalable, and adhere to best practices in ethical AI development. Conduct testing, performance benchmarking, and iterative refinements of AI models and pipelines. Stay updated with the latest advancements in AI/ML, NLP, and cloud technologies and recommend integration strategies for emerging tools and techniques. Create technical documentation and presentations to effectively communicate AI concepts to stakeholders. Required Skills Key Skills and Qualifications: AI/ML Expertise: Proven experience in developing, fine-tuning, and deploying AI/ML models, focusing on NLP, Generative AI, and Time Series Forecasting. Prompt Engineering: Proficiency in designing, testing, and optimizing prompts for LLMs. Data Analysis: Strong ability to process and interpret large and complex datasets, including time series data, for AI model training and validation. Programming: Proficiency in Python and experience with AI/ML frameworks like TensorFlow, PyTorch, and scikit-learn. NLP Techniques: Understanding of tokenization, embeddings, transformer-based models (e.g., BERT, GPT, LLaMA), and RAG workflows. Vector Databases: Experience with Weaviate, Pinecone, FAISS, or similar VectorDBs for document retrieval and storage. LangGraph & GenAI Frameworks: Hands-on experience with LangGraph, LangChain, HuggingFace Transformers, OpenAI API, and other Generative AI tools. Cloud Deployment: Familiarity with deploying AI solutions on AWS, GCP, or Azure. Time Series Forecasting: Experience with ARIMA, LSTM, Prophet, and other forecasting techniques. Model Training & Fine-Tuning: Ability to train and fine-tune machine learning models, including large language models (LLMs), to enhance performance and accuracy. Problem-Solving & Collaboration: Strong analytical, problem-solving, and teamwork skills to work effectively in a cross-functional environment. Preferred Skills Experience in implementing RAG workflows and integrating generative AI with retrieval-based systems. Familiarity with ethical AI principles and compliance frameworks. Knowledge of additional programming languages such as JavaScript or SQL. Proficiency in MLOps practices for automating AI/ML pipelines and lifecycle management. Experience in developing AI-driven applications for real-world industry use cases. Skills: retrieval-augmented generation (rag),neuro-linguistic programming (nlp),data analysis,collaboration,programming,forecasting,prompt engineering,pytorch,cloud deployment,generative ai frameworks,programming in python,time series forecasting,langgraph & genai frameworks,vector databases (weaviate, pinecone, faiss),problem-solving & collaboration,langgraph & genai frameworks (langchain, huggingface transformers, openai api),ai ml,gen ai,vector databases,time series forecasting (arima, lstm, prophet),model training & fine-tuning,scikit-learn,problem-solving,tensorflow,langgraph,cloud deployment (aws, gcp, azure),nlp techniques,programming (python),mlops,ai/ml expertise

We are looking for a Data Scientist to help us gain useful insight from raw data. Data scientists' responsibilities include working with the data science team, planning projects, and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Responsibilities Responsible for overseeing the data scientists' team and data specialists. Teach, lead, and counsel colleagues on new techniques or solutions. Collaborate with data and software engineers to enable the deployment of sciences and technologies that will scale across the company's ecosystem. Responsible for the conception, planning, and prioritizing of data projects. Responsible for building analytic systems and predictive models, as well as experimenting with new models and techniques. Ensure that data projects align with organizational goals. Requirements Master's degree in Computer Science, Operations Research, Econometrics, Statistics, or related technical field. 3+ years of experience solving analytical problems using quantitative approaches. Experience communicating quantitative analysis results. Knowledge of relational databases and SQL. Development experience in any scripting language (PHP, Python, Perl, etc. ). Knowledge of statistics (e. g., hypothesis testing, regression). Experience manipulating data sets through statistical software (ex., R, SAS) or other methods. Must Have Programming - Python (Preferred) / R. ML Models - i. Regression - Linear, Logistic, Multinomial, Mixed effect. Classification - Bagging and Boosting (Random Forest), Decision tree, SVM. Clustering - K-Means, hierarchical, DB-Scan. Time series - ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM, Neural Networks (Deep learning), Naive Bayes, Excel, and SQL. Dimensionality Reduction - PCA, SVD, etc. Optimization Techniques - Linear programming, Gradient Descent, Genetic Algorithm. Cloud - Understanding of Azure / AWS offerings, setting up an ML pipeline in the cloud. Good To Have Visualization - Tableau / Power BI / Looker / QlikView. Data management - HDFS, Spark, Advanced Excel. Agile Tools - Azure DevOps, JIRA, Pyspark, Big Data/Hive Database. IDE: PyCharm. This job was posted by Debapti Roy from mPokket.

Dear Candidate, Greetings from Global Healthcare Billing Partners Pvt Ltd! We are pleased to inform you about Opening with the Global Healthcare for the profile of CHARGE ENTRY & PAYMENT POSTING!!! Experience : 1Years - 6 Years Qualification : Any Graduate Notice: Immediate Joiner. Essential Requirement :- Associate should have worked Experience in Charge entry & Payment Posting with good knowledge of medical billing process. Location: Velachery & Vepery Shift: Day Contact Name : MALINI HR Contact Details - 9003239650 / 8925808598 (Call or Whatsapp) NOTE : (only Medical billing experience with 1Yrs are eligible) Regards MALINI HR GLOBAL

Primary Skills Time Series Forecasting : Applying models like ARIMA, Prophet, or LSTM for month-on-month estimations Machine Learning : Building and deploying ML models for forecasting and cost optimization Python Programming : For data manipulation, modeling, and automation (Pandas, NumPy, scikit-learn) CDN Domain Knowledge : Understanding content delivery networks, traffic patterns, and cost structures Power BI : Designing dashboards for CDN usage reporting (regional, brand-level, etc.) Data Analysis & Modeling : Statistical analysis, feature engineering, and model evaluation Cost Optimization Techniques : Using ML to model and optimize CDN allocation and expenses SQL : Querying structured data for reporting and model input Secondary Skills These enhance effectiveness and collaboration but are not strictly mandatory: Cloud Platforms : Familiarity with Azure, AWS, or GCP for data storage and compute ETL & Data Wrangling : Preparing and transforming data from multiple sources Version Control : Using Git for code collaboration and tracking Agile Methodologies : Working in sprints, using tools like JIRA or Confluence Communication Skills : Explaining technical insights to non-technical stakeholders Collaboration Tools : Experience with Teams, Slack, or similar platforms This job is provided by Shine.com

Mandatory leadership experience is required & responsible for managing a team of 50+ associates under at least 2-3 team leads. Responsible for timely and accurate posting of all payments. Experience in Payment posting, Denials Postings and Insurance rejections & Claims. Responsible to handle team and maintain teams production & quality, client coordination Should Possess extensive knowledge in Reviewing Explanation of Benefits (EOB) and Electronic remittance advice (ERA) documents, matches with electronic funds transfers (EFTs) and post payment to appropriate accounts. This Role involves extensive knowledge in Payment and Denial Posting, ERA posting, Correspondence posting, Insurance Portals, Bank Reconciliations, Marchant portals, Refund process, Statement and Collection process, EOM Reporting. Excellent skill sets required in Microsoft products, especially excel spreadsheet for reports and analyze data using tools like VLOOKUP. Pivot table etc. The right candidate should be able to handle the work pressure during End of Month and will take the challenge to meet the day-to-day deliverables. Ensuring the Daily/Weekly and Monthly reports are to be shared with the stakeholders in a timely manner and within the given time. Good communication and interpersonal skills especially with the team members and clients. Preferred Only Immediate Joiner Salary will not be a constraint to a right candidate & at par with the Industry standard.

Job Responsibilities: Claim Verification: Verify and review healthcare claims to ensure accuracy and completeness. Learn to identify common billing errors and discrepancies in claim submissions. Initiate Follow-up Calls: Make outbound calls to insurance companies to inquire about the status of claims. Gain exposure to professional communication and develop rapport with insurance representatives. Research Denials and Underpayments: Investigate reasons for claim denials and underpayments. Work closely with senior AR Callers to understand denial codes and resolution strategies. Assist in Appeal Preparation: Support in the preparation of appeal packets for denied or underpaid claims. Learn the documentation and submission process for appeals. Claim Corrections: Understand the basics of correcting errors on claims and resubmitting them. Collaborate with team members to rectify common billing mistakes. Documentation and Reporting: Maintain accurate records of communication and actions taken in the claims billing system. Assist in generating basic reports related to claim status and follow-up activities. Training and Skill Development: Actively participate in training programs provided by the company. Continuously enhance knowledge of medical billing and coding practices.

Location: Gurugram, India Position Summary We are seeking a highly motivated and analytical Quant Analyst to join Futures First. The role involves supporting development and execution of quantitative strategies across financial markets. Job Profile Statistical Arbitrage & Strategy Development Design and implement pairs, mean-reversion, and relative value strategies in fixed income (govvies, corporate bonds, IRS). Apply cointegration tests (Engle-Granger, Johansen), Kalman filters, and machine learning techniques for signal generation. Optimize execution using transaction cost analysis (TCA). Correlation & Volatility Analysis Model dynamic correlations between bonds, rates, and macro variables using PCA, copulas, and rolling regressions. Forecast yield curve volatility using GARCH, stochastic volatility models, and implied-vol surfaces for swaptions. Identify regime shifts (e.g., monetary policy impacts) and adjust strategies accordingly. Seasonality & Pattern Recognition Analyse calendar effects (quarter-end rebalancing, liquidity patterns) in sovereign bond futures and repo markets. Develop time-series models (SARIMA, Fourier transforms) to detect cyclical trends. Back Testing & Automation Build Python-based back testing frameworks (Backtrader, Qlib) to validate strategies. Automate Excel-based reporting (VBA, xlwings) for P&L attribution and risk dashboards. Integrate Bloomberg/Refinitiv APIs for real-time data feeds. Requirements Education Qualifications B.Tech Work Experience 0-3 years Skill Set Must have: Strong grasp of probability theory, stochastic calculus (Itos Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH). Must have: Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques. Preferred: Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning). Libraries: NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models). Back testing: Backtrader, Zipline, or custom event-driven frameworks. Data handling: SQL, Dask (for large datasets). Power Query, pivot tables, Bloomberg Excel functions (BDP, BDH). VBA scripting for various tools and automation. Experience with C /Java (low-latency systems), QuantLib (fixed income pricing), or R (statistical). Yield curve modelling (Nelson-Siegel, Svensson), duration/convexity, OIS pricing. Credit spreads, CDS pricing, and bond-CDS basis arbitrage. Familiarity with VaR, CVaR, stress testing, and liquidity risk metrics. Understanding of CCIL, NDS-OM (Indian market infrastructure). Ability to translate intuition and patterns into quant models. Strong problem-solving and communication skills (must explain complex models to non-quants). Comfortable working in a fast-paced work environment. Work hours will be aligned to APAC Markets.

Dear Candidate, Greetings from Global Healthcare Billing Partners Pvt Ltd! We are pleased to inform you about Opening with the Global Healthcare for the profile of CHARGE ENTRY &PAYMENT POSTING Experience : 0.6Year - 4 Years Qualification : Any Graduate Essential Requirement :- Associate should have worked Experience in Charge Entry & Payment Posting with good knowledge of medical billing process. Location: Velachery Shift: Day Contact Name : MALINI HR Contact Details - 9003239650 / 8925808598 NOTE : (only Medical billing experience are eligible) Regards GLOBAL MALINI HR 90032 39650

ONLY IMMEDIATE JOINERS: Role & responsibilities Design, train, and deliver data science solutions using all modalities (tabular, text, image) Working hands on advanced analytics projects using python Mentor and work with a team of data scientists and data engineer to build advanced analytical solutions for clients Analyse experimental results, iterate, and refine models to create significant business impact Understanding and formulating the business problem into analytics framework Managing stakeholders, and communicating insights to business and technical teams Preferred candidate profile Mandatory: Time Series Forecasting, Demand Forecasting, Python, Pricing Analytics Customer and Marketing Analytics Pricing and Promotion Analytics Supply Chain Analytics Demand Forecasting / Production Planning / Procurement / Inventory Planning / Logistics Digital Analytics Predictive Maintenance / Predictive Quality In-depth understanding of various machine learning algorithms Ability to write robust codes in Python and familiarity with standard machine learning libraries is a plus Excellent communication and interpersonal skills to interact with internal and external stakeholders Good team player, self-motivated, able to ideate and work on various initiatives Perks and benefits

Roles & Responsibilities: Lead end-to-end development of demand forecasting models using classical time series (ARIMA, Exponential Smoothing), machine learning, and demand sensing techniques using market intelligence and historical sales data. Design and implement mathematical optimization solutions for production planning, scheduling and network optimization across manufacturing and distribution points. Work directly with supply chain leaders to translate business problems into quantitative models and deliver measurable improvements in service levels, cost, and efficiency. Deploy and maintain solutions in production environments, collaborating with engineering and business intelligence teams. Quantify business impact (e.g. xx% reduction in stockouts, xx% reduction in idle stock). Technical & Functional Skills: 6+ years of experience in demand forecasting and supply chain optimization in manufacturing or pharma domain. Strong demand forecasting expertise- Time series, machine learning and deep learning models. Strong programming in Python, SQL; familiarity with GCP or Azure. Deep knowledge of supply chain processes - production planning, inventory management, and logistics. Experience with simulation tools (e.g. Arena) is a plus. Ability to communicate complex models to non-technical stakeholders and influence decision-making. Good to have Expertise in solvers (e.g. Gurobi, CPLEX/ILOG, Hexaly) for MILP and Constraint-based optimization. About the Department | Digital Process and Excellence (DPEx): Our digital transformation journey is led by the DPEx team and is structured along the lines of Digitalize the Core and Transform with Digital. With a mandate to ensure continuous process improvement and drive patient centric innovation, it spans all functions and operations. In other words, you could be working on projects to expedite research outcomes one day, designing customer engagement platforms the next and simplifying warehouse processes the third. Some its priorities are: Reimagine Dr. Reddy’s as a ‘platform-based’ organization. Create Data as an asset that brings competitive advantage and business impact. Create Digital solutions that make the lives of our patients and customers easier and better.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role The Global Brand Analytics Team at Anheuser-Busch InBev (AB InBev) is tasked with helping strengthen AB InBev’s brands across the globe. The solutions we provide aim to extract insights and give guidance on actionable from all our brand related data. The derived data-driven insights play a pivotal role in empowering our Marketing teams to make well-informed decisions backed by cutting edge modelling techniques and thorough analysis. Key tasks & accountabilities Execute coding skills to develop ML/time-series models. Focus on developing end-to-end analytical solution and present them to business partners/stakeholders. Should have consultative mindset to come up with solutions that can be easily understood and interpreted by business users. Research on the newer technologies and algorithms, to provide better solutions to the current problems. Interact and manage expectations of multiple stakeholders, building compelling narratives and help drive value for businesses by helping them strengthen brands on ground. Qualifications, Experience, Skills Level Of Educational Attainment Required Degree in business analytics / data science / statistics / economics and / or degree in Engineering, Mathematics or Computer Science. Previous Work Experience Minimum 3 years of experience, 2 years in to Data Science must. Hands-on experience in implementation of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques) and time-series algorithms (e.g. ARIMA, ARIMAX, UCM, Holt-Winters and others). Strong programming skills with working knowledge of SQL, Python. Excellent problem-solving and analytical mindset. Strong communication and interpersonal skills. Strong story boarding skills. Preferred Skills Marketing Analytics background in FMCG And above all of this, an undying love for beer! We dream big to create future with more cheers.

We are currently seeking talented individuals for multiple openings in Payment Posting, Denial Specialist, and Demo & Charge Entry roles. Payment Posting Specialist (End-to-End Process) - 10 positions available Denial Specialist (End-to-End Process) - 10 positions available Demo & Charge Entry Specialist - 10 positions available We are looking for candidates who can join immediately.

Lead AI Engineer (GenAI & AI/ML Focus) Experience : 5+ years (with at least 1-2 years in GenAI/Agentic AI) About the Role We’re seeking a Lead AI Engineer to drive the design, development, and scaling of intelligent systems powered by Generative AI and Agentic AI architectures. You’ll play a central role in shaping the technical foundation of our AI solutions, guiding junior engineers, leading experiments, and taking end-to-end ownership of core components such as prompt infrastructure, model routing logic, RAG systems, and autonomous agents. This role blends deep hands-on engineering with architectural vision and technical leadership. If you’re someone who enjoys building fast, mentoring others, and solving tough AI problems across infrastructure, experimentation, and deployment, this role is for you. What You’ll Do Architect and implement LLM-based GenAI systems: prompt pipelines, retrieval flows, model selection, fallback mechanisms, prompt optimization, prompt versioning, modular prompts, and tool orchestration strategies Design and lead multi-agent systems with memory, tool-use, task adaptation, and inter-agent collaboration using frameworks like LangGraph, CrewAI, AutoGen, LangChain Architect, deploy, and continuously evolve retrieval-augmented generation (RAG) pipelines, handle model substitution, evaluation, prompt versioning, and runtime fallback strategies Drive the creation of internal prompt libraries, LLM orchestration logic, and evaluation harnesses Collaborate on fine-tuning, embedding optimization, and multi-model substitution workflows Collaborate on model evaluation, benchmarking, and agentic stress testing in production Own end-to-end AI applications involving image, text, tabular, and signal data, working with both unimodal and multi-modal inputs Develop solutions in computer vision (e.g., OCR, classification, object detection) and multi-modal AI (e.g., text + image pipelines) Design and evaluate statistical models and classical ML systems, including time-series forecasting and predictive analytics Lead development of signal processing or anomaly detection systems (e.g., for sensor, telemetry, or log data) Build & support cost-optimization, compliance, and monitoring in GenAI deployments Mentor and unblock junior AI engineers and interns through code reviews, architecture sessions, and contribute to team knowledge base and enforce internal best practices Work closely with product, data, and platform teams to bring AI prototypes to production Partner with Data, Product, and Platform teams to ship enterprise-grade AI modules Who Should Apply You are a builder with: Minimum qualification: Bachelor’s or Master’s degree Disciplines: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or any other quantitative or computational field 5+ years of professional experience in AI/ML development (with 1-2+ years in GenAI or Agentic systems) Proven experience architecting and shipping real-world AI applications at scale Strong mentoring skills and a product-focused engineering mindset An interest in shaping the long-term AI strategy while delivering short-term wins Must-Have Skills Strong Python development skills with emphasis on modular, testable design Deep familiarity with LLM APIs, prompt frameworks (e.g., LangChain, LangGraph, CrewAI), and RAG pipelines Experience building systems for model selection, prompt fallback, tool orchestration, and versioning Familiarity with MLOps pipelines, ML monitoring, and model lifecycle management Experience in building and optimizing RAG architectures and vector database integrations Knowledge of model selection, fallbacks, prompt versioning, and task decomposition Strong grasp of autonomous agent design, reasoning, tool use, and multi-agent protocols Exposure to near real-time signal/voice processing, filtering, or event-based triggers (e.g., anomaly/event detection) Practical knowledge of statistical modeling, forecasting (ARIMA, Prophet, ML-based), or classical ML pipelines 5+ years in AI/ML engineering, including 1–2+ years working directly on GenAI/Agentic AI projects Preferred Skills Experience with multi-agent collaboration patterns (e.g., A2A, MCP) Deployment experience on GenAI platforms like OpenAI, Claude, Vertex AI, Amazon Bedrock, or Azure GenAI Familiarity with serverless deployment, egress handling, and LLM usage constraints Exposure to evaluation frameworks, benchmarking suites, or internal testing systems Experience integrating AI flows with external systems (BI tools, dashboards, APIs, automation platforms) Prior experience designing multi-modal pipelines combining vision, text, or sensor data Bonus / Good-to-Have Hands-on with fine-tuning workflows (LoRA, PEFT, etc.) Understanding of vector database internals and hybrid retrieval methods Familiarity with CV/multi-modal AI workflows using OpenCV, TorchVision, CLIP, BLIP, or related libraries Prior experience contributing to open-source GenAI libraries or leading internal tool development Why Join Us Help shape the next-gen AI stack from the ground up Work in a fast-moving environment with real ownership and autonomy Collaborate with a cross-disciplinary team at the cutting edge of GenAI and agentic systems Be part of an organization that values experimentation, modularity, and long-term impact Interested candidates can share the CV on shikha.rana@antiersolutions.com