1829 Mlflow Jobs - Page 9

You are an experienced AI Application Architect responsible for leading the design and integration of AI/ML capabilities into enterprise applications. Your main objective is to architect intelligent, scalable, and reliable AI solutions that are in line with both business goals and technical strategies. You will work closely with data scientists, ML engineers, and application developers to ensure seamless end-to-end solutions. Additionally, you will be required to select and implement appropriate AI frameworks, APIs, LLMs, and infrastructure tools, as well as drive architecture decisions related to GenAI, NLP, CV, predictive analytics, and agentic AI systems. You will also establish MLOps pipelines for training, testing, and deploying models at scale while ensuring compliance with AI ethics, privacy laws, and data governance policies. Furthermore, you will evaluate emerging technologies, tools, and platforms for enterprise use and act as a technical advisor to leadership on AI opportunities and risks. In terms of required skills, you should have a strong background in AI/ML architecture and solution design, along with hands-on experience in ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Proficiency in LLMs and generative AI tools like OpenAI, Azure OpenAI, LangChain, and Hugging Face is necessary. A solid programming background in Python (FastAPI, Flask) and familiarity with Java/Node.js are essential. Experience with cloud platforms (AWS/GCP/Azure) and ML toolkits like SageMaker, Azure ML, and Vertex AI is also crucial. Additionally, a good understanding of microservices, REST APIs, GraphQL, and event-driven architecture is required. Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Weaviate, as well as proficiency with CI/CD, Docker, Kubernetes, MLflow, Airflow, or similar tools, is expected. Preferred qualifications include experience with multi-agent systems, LangChain, Autogen, or Agentic AI frameworks, familiarity with data governance, model drift detection, and performance monitoring, and prior experience in industries like BFSI, Retail, Healthcare, or Manufacturing. Education-wise, a Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or a related field is required. Certifications in AI/ML, cloud (AWS/GCP/Azure), or MLOps are considered a plus.,

Job Summary: We are seeking a talented and driven Machine Learning Engineer to design, build, and deploy ML models that solve complex business problems and enhance decision-making capabilities. You will work closely with data scientists, engineers, and product teams to develop scalable machine learning pipelines, deploy models into production, and continuously improve their performance. Key Responsibilities: Design, develop, and deploy machine learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks. Collaborate with data scientists to prepare and preprocess large-scale datasets for training and evaluation. Implement and optimize machine learning pipelines and workflows using tools like MLflow, Airflow, or Kubeflow. Integrate models into production environments and ensure model performance, monitoring, and retraining. Conduct A/B testing and performance evaluations to validate model accuracy and business impact. Stay up-to-date with the latest advancements in ML/AI research and tools. Write clean, efficient, and well-documented code for reproducibility and scalability. Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Strong knowledge of machine learning algorithms, data structures, and statistical methods. Proficient in Python and ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost). Experience with data manipulation libraries (e.g., pandas, NumPy) and visualization tools (e.g., Matplotlib, Seaborn). Familiarity with cloud platforms (AWS, GCP, or Azure) and model deployment tools. Experience with version control systems (Git) and software engineering best practices. Preferred Qualifications: Experience in deep learning, natural language processing (NLP), or computer vision. Knowledge of big data technologies like Spark, Hadoop, or Hive. Exposure to containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. Familiarity with MLOps practices and tools.

About the Role: Acrocede Technologies Pvt Ltd is looking for a highly experienced AI/ML Architect to be deployed to our client Techversant , a global leader in digital transformation and technology services. This is a strategic, client-facing leadership role where you’ll lead the design and delivery of end-to-end AI solutions across cutting-edge domains. Work Mode : Remote or Onsite, depending on candidate location What You'll Do Work directly with clients to understand business problems and propose AI-driven solutions Architect and lead end-to-end AI/ML systems – from data ingestion to model deployment Guide AI/ML model selection, training, testing, and integration Build and mentor a high-performing AI team Drive delivery excellence using Agile methodologies and MLOps best practices Key Skills Required Strong expertise in AI/ML/DL , including models like CNN, RNN, Transformers, LLMs Programming: Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face AI architecture design: microservices, APIs, cloud-native stacks Experience with AWS, Azure, or GCP ML services Familiarity with vector databases , MLOps tools (MLflow, Kubeflow, etc.), and data engineering (Spark, Kafka, Databricks) Excellent stakeholder communication and leadership skills Cloud certifications (AWS/GCP/Azure AI) preferred Good to Have Experience with Generative AI / LLMs / RAG / LangChain / Stable Diffusion Prompt engineering, fine-tuning, RLHF knowledge Previous contributions to research, publications, open-source, or AI certifications Understanding of explainable AI , ethical AI, and compliance

About the Role: We are looking for a highly skilled AI/ML Developer to join the core product team of QAPilot.io. The ideal candidate should come from a product-based or AI-first company, with a strong academic background from institutes like IITs, NITs, IIITs, or other Tier-1 engineering colleges. You will work on real-world AI problems related to test automation, software quality, and predictive engineering. Key Responsibilities: Design, build, and deploy machine learning models for intelligent QA automation Work on algorithms for test case optimization, bug prediction, pattern recognition, and data-driven QA insights Apply techniques from supervised/unsupervised learning, NLP, and deep learning Integrate ML models into the product using scalable and production-ready code Continuously improve model performance through experimentation and feedback loops Collaborate with full-stack developers, product managers, and QA experts Explore LLMs, transformers, and generative AI for advanced test data generation and analysis Required Skills & Qualifications: B.Tech / M.Tech / MS in Computer Science, Data Science, or related fields from IIT/NIT/IIIT or other top-tier institutes 3+ years of experience as an AI/ML Developer, preferably in product or AI-centric companies Strong proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch) Experience in NLP, LLMs, or generative AI (preferred) Hands-on with ML lifecycle: data wrangling, model training, evaluation, and deployment Familiarity with MLOps tools like MLFlow, Docker, Airflow, or cloud platforms (AWS/GCP) Prior exposure to software testing, DevOps, or developer tooling is a plus Strong analytical skills, attention to detail, and curiosity to solve open-ended problems Portfolio, GitHub, or project links demonstrating AI/ML expertise are desirable Why Join QAPilot.io: Work on an innovative AI product transforming the software QA ecosystem Join a high-impact, product-oriented engineering culture Solve challenging AI problems with real user value Collaborate with top talent from the tech and AI ecosystem Competitive salary, learning-focused environment, and growth opportunities To Apply: Please send your updated resume and any supporting links (GitHub, projects, publications).

Role Summary 1. Demonstrate solid proficiency in Python development, writing clean, maintainable code. 2. Collaborator in the design and implementation of AI-driven applications leveraging large language models (LLMs). 3. Develop and maintain Django-based RESTful APIs to support backend services. 4. Integrate with LLM provider APIs (e.g., GPT, Claude, Cohere) and agent frameworks (LangChain, AgentStudio). 5. Build and optimize data pipelines for model training and inference using Pandas, NumPy, and Scikit-learn. 6. Ensure robust unit and integration testing via pytest to maintain high code quality. 7. Participate in agile ceremonies, contributing estimations, design discussions, and retrospectives. 8. Troubleshoot, debug, and optimize performance in multi-threaded and distributed environments. 9. Document code, APIs, and data workflows in accordance with software development best practices. 10. Continuously learn and apply new AI/ML tools, frameworks, and cloud services. Key Responsibilities 1. Write, review, and optimize Python code for backend services and data science workflows. 2. Design and implement Django REST APIs, ensuring scalability and security. 3. Integrate LLMs into applications: handle prompt construction, API calls, and result processing. 4. Leverage agent frameworks (LangChain, AgentStudio) to orchestrate complex LLM workflows. 5. Develop and maintain pytest suites covering unit, integration, and end-to-end tests. 6. Build ETL pipelines to preprocess data for model training and feature engineering. 7. Work with relational databases (PostgreSQL) and vector stores (FAISS, Weaviate, Milvus). 8. Containerize applications using Docker and deploy on Kubernetes or serverless platforms (AWS, GCP, Azure). 9. Monitor and troubleshoot application performance, logging, and error handling. 10. Collaborate with data scientists to deploy and serve ML models via FastAPI or vLLM. 11. Maintain CI/CD pipelines for automated testing and deployment. 12. Engage in technical learning sessions and share best practices across the team. Desired Skills & Qualifications - 1–3 years of hands-on experience in Python application development. - Proven pytest expertise, with a focus on test-driven development. - Practical knowledge of Django (or FastAPI) for building RESTful services. - Experience with LLM APIs (OpenAI, Anthropic, Cohere) and prompt engineering. - Familiarity with at least one agent framework (LangChain, AgentStudio). - Working experience in data science libraries: NumPy, Pandas, Scikit-learn. - Exposure to ML model serving tools (MLflow, FastAPI, vLLM). - Experience with container orchestration (Docker, Kubernetes, Docker Swarm). - Basic understanding of cloud platforms (AWS, Azure, or GCP). - Knowledge of SQL and database design; familiarity with vector databases. - Eagerness to learn emerging AI/ML technologies and frameworks. - Excellent problem-solving, debugging, and communication skills. Education & Attitude - Bachelor’s or Master’s in Computer Science, Data Science, Statistics, Mathematics, or related field. - Growth-mindset learner: proactive in upskilling and sharing knowledge. - Strong collaboration ethos and adaptability in a fast-paced AI environment.

Lead Sofware Engineer - Simulations(with ML Background) - Global Data Analytics, Technology (Maersk) This position will be based in India – Bangalore/Pune A.P. Moller - Maersk A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains. Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too. The Brief We are seeking a Lead Software Engineer with deep experience in simulation systems and a solid foundation in machine learning to lead the architecture and development of our next-generation simulation and digital twin platforms. This role blends technical leadership with hands-on engineering, guiding the design of simulation systems that model real-world environments and power intelligent, ML-driven decision-making. You’ll be responsible for leading simulation efforts that generate actionable insights, synthetic data, and predictive capabilities — while also influencing how ML models are built, trained, and deployed within these environments. What I'll be doing – your accountabilities/responsibilities? Architect and lead simulation platforms that model complex systems across time, agents, and interactions. Bridge simulation systems with ML workflows: data generation, model training/testing, reinforcement learning, etc. Define system architecture, technology choices, and software patterns for scalable, high-performance simulation and ML integration. Collaborate with ML engineers, data scientists, and domain experts to enable closed-loop simulations for forecasting, optimization, and control. Lead cross-functional engineering efforts across simulation, data, and ML infrastructure teams. Mentor engineers across disciplines, setting technical standards and fostering a high-performance culture. Own end-to-end delivery of simulation-enabled intelligent systems — from ideation to production. Develop and optimize algorithms for discrete-event simulation, agent-based modeling. Support scenario testing, what-if analysis, and optimization workflows using simulation outputs. Ensure models are modular, extensible, and easily integrated with external services/platforms (e.g., dashboards, analytics, AI agents). Foundational /Must Have Skills Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field. 12+ years of software engineering experience, with 3+ years leading teams or major initiatives. Demonstrated experience in simulation platforms (e.g., SimPy, Mesa, CARLA, Unity, AnyLogic, or custom-built engines). Strong programming skills in Python (required); additional languages like C++, Rust, or Julia are a plus. Deep understanding of ML principles — model pipelines, data engineering, evaluation, and deployment. Experience working with synthetic data, simulators for ML training/testing, or RL environments (e.g., OpenAI Gym, Isaac Sim, Unity ML-Agents). Solid grasp of software architecture, distributed systems, and CI/CD pipelines. Preferred To Have Experience with reinforcement learning, decision-making under uncertainty, or control systems. Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and MLOps tools (e.g. MLflow, Weights & Biases). Background in simulation-heavy domains such as robotics, logistics, autonomous systems. Familiarity with cloud infrastructure (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Strong communication and cross-functional leadership skills — able to align engineers, ML teams, and product stakeholders. As a performance-oriented company, we strive to always recruit the best person for the job – regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams. Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.

This role is for one of Weekday's clients Min Experience: 5 years Location: Bengaluru JobType: full-time Requirements We are looking for an experienced Data Scientist with a strong background in the CPG (Consumer Packaged Goods) or Retail domain , focusing on category and product analytics , forecasting , and machine learning workflows . The ideal candidate will possess advanced analytical skills, business acumen, and hands-on expertise in modern data science tools and platforms such as Python, SQL, Databricks, PySpark , and CI/CD ML pipelines . As a Data Scientist, you will be responsible for generating actionable insights across product assortment, category performance, sales trends, and customer behaviors. Your work will directly influence decision-making for new product launches , inventory optimization , campaign effectiveness , and category planning , enabling our teams to enhance operational efficiency and drive business growth. Key Responsibilities Category & Product Analytics: Conduct deep-dive analysis into product assortment, SKU performance, pricing effectiveness, and category trends. Evaluate new product launches and provide recommendations for optimization based on early performance indicators. Sales Data Analysis & Forecasting: Analyze historical and real-time sales data to identify key growth drivers, seasonality, and demand patterns. Build statistical and ML-based models to forecast demand and category-level performance at multiple aggregation levels. Customer Analytics (Nice to Have): Analyze loyalty program data and campaign performance metrics to assess customer retention and ROI of promotions. ML Model Development & Deployment: Design, build, and deploy machine learning models using Python and PySpark to address business problems in forecasting, product clustering, and sales optimization. Maintain and scale CI/CD pipelines for ML workflows using tools like MLflow, Azure ML, or similar. Data Engineering and Tooling: Develop and optimize data pipelines on Databricks and ensure reliable data ingestion and transformation for analytics use cases. Use SQL and PySpark to manipulate and analyze large datasets with performance and scalability in mind. Visualization & Stakeholder Communication: Build impactful dashboards using Power BI (preferred) to enable self-service analytics for cross-functional teams. Translate data insights into clear, compelling business narratives for leadership and non-technical stakeholders. Collaboration & Strategic Insights: Work closely with category managers, marketing, and supply chain teams to align data science initiatives with key business objectives. Proactively identify opportunities for innovation and efficiency across product and sales functions. Required Skills & Qualifications Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related quantitative field. 5+ years of experience in applied data science, preferably in CPG/Retail/FMCG domains. Proficient in Python, SQL, Databricks, and MLflow. Experience with PySpark and Azure ML is a strong plus. Deep experience with time-series forecasting, product affinity modeling, and campaign analytics. Familiarity with Power BI for dashboarding and visualization. Strong storytelling skills, with the ability to explain complex data-driven insights to senior stakeholders. Solid understanding of challenges and opportunities within the retail and FMCG space. Ability to work independently as well as in cross-functional teams in a fast-paced environment.

Greetings ! One our our client TOP MNC Giant looking for GEN AI and Machine Learning Engineer's Important Notes: Please share only those profiles who can join immediately or within 7 days. Base Locations: Gurgaon and Bengaluru (hybrid setup 3 days work from office). Role : Associate and Sr Associate L1/L2 (Multiple Positions) SKILLS :  Bachelor's or master’s degree in Computer Science, Data Science, Engineering, or a related field.  Experience on Agentic AI/ Frameworks  Strong programming skills in languages such as Python, SQL/NoSQL etc.  Build analytical approach based on business requirements, then develop, train, and deploy machine learning models and AI algorithms  Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc.  Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras.  Knowledge of math, probability, and statistics.  Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms.  Exposure in developing API using Flask/Django.  Good experience in cloud infrastructure such as AWS, Azure or GCP  Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model) GOOD TO HAVE : Experience with MLOps: MLFlow, Kubeflow, CI/CD Pipeline etc. Good to have experience in Docker, Kubernetes etc Exposure in HTML, CSS, Javascript/JQuery, Node.js, Angular/React Experience in Flask/Django is a bonus RESPONSIBILITIES : Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions.  Develop, implement, and deploy AI/ML solutions.  Preprocess and analyze large datasets to identify patterns, trends, and insights.  Evaluate, validate, and optimize AI/ML models to ensure their accuracy, efficiency, and generalizability.  Deploy applications and AI/ML model into cloud environment such as AWS/Azure/GCP etc.  Monitor and maintain the performance of AI/ML models in production environments, identifying opportunities for improvement and updating models as needed.  Document AI/ML model development processes, results, and lessons learned to facilitate knowledge sharing and continuous improvement. INTERESTED CANDIDATES PERFECT MATCH TO THE JD AND WHO CAN JOIN ASAP ONLY DO APPLY ALONG WITH BELOW MENTIONED DETAILS : Total exp : Relevant exp in AI/ ML : Applying for Gurgaon and Bengaluru : Open for Hybrid : Current CTC : Expected CTC : Can join ASAP : Will call you once we receive your updated profile along with above mentioned details. Thanks, Venkat Solti solti.v@anlage.co.in

ROLES & RESPONSIBILITIES Qualifications and Skills: •Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field. 5+ years of hands-on experience in data science or machine learning roles. Strong proficiency in Python or R, with deep knowledge of libraries like scikit-learn, pandas, NumPy, TensorFlow, or PyTorch. Proficient in SQL and working with relational databases. Solid experience with Azure cloud platforms and data pipeline tools. Strong grasp of statistical methods, machine learning algorithms, and model evaluation techniques. Excellent communication and storytelling skills with the ability to influence stakeholders. Proven track record of delivering impactful data science solutions in a business setting. Preferred Qualifications: Experience working in industries such as [logistics, aerospace, marketing, etc.]. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Knowledge of data visualization tools (e.g., Tableau, Power BI, Plotly). Responsibilities and Duties Model Development: Design, build, and deploy scalable machine learning models to solve key business challenges (e.g., customer churn, recommendation engines, pricing optimization). Data Analysis: Perform exploratory data analysis (EDA), statistical testing, and feature engineering to uncover trends and actionable insights. Project Leadership: Lead end-to-end data science projects, including problem definition, data acquisition, modeling, and presentation of results to stakeholders. Cross-functional Collaboration: Partner with engineering, product, marketing, and business teams to integrate models into products and processes. Mentorship: Guide and mentor junior data scientists and analysts, helping them grow technically and professionally. Innovation: Stay current with the latest data science techniques, tools, and best practices. Evaluate and incorporate new technologies when appropriate. Communication: Translate complex analyses and findings into clear, compelling narratives for non-technical stakeholders. EXPERIENCE 8-11 Years SKILLS Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): Data Science ABOUT THE COMPANY Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP). Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Kraków, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.

Location Gurugram, Jaipur Employment Type Full time Location Type Hybrid Department Engineering For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram. Position Description: We are seeking a Machine Learning Engineer to join our growing AI team at PAR . This role will focus on developing and scaling GenAI-powered services, recommender systems, and ML infrastructure that fuel personalized customer engagement. You will work across teams to drive technical excellence and real-world ML application impact. Position Location: Jaipur / Gurgaon Reports To: [Hiring Manager Title – e.g., Head of AI or Senior Director, AI Engineering] What We’re Looking For: Entrees (Requirements): Master’s or PhD in Computer Science, Machine Learning, or a related field 3+ years of experience delivering production-ready machine learning solutions Deep understanding of ML algorithms , recommender systems , and NLP Experience with LLM frameworks (Hugging Face Transformers, LangChain, OpenAI API, Cohere) Strong proficiency in Python , including object-oriented design and scalable architecture Advanced expertise in Databricks : notebooks, MLflow tracking, data pipelines, job orchestration Hands-on experience with cloud-native technologies – preferably AWS (S3, Lambda, ECS/EKS, SageMaker) Experience working with modern data platforms : Delta Lake, Redis, Elasticsearch, NoSQL, BigQuery Strong verbal and written communication skills to translate technical work into business impact Flexibility to collaborate with global teams in PST/EST time zones when required With a Side of (Additional Skills): Familiarity with vector databases (FAISS, ChromaDB, Pinecone, Weaviate) Experience with retrieval-augmented generation (RAG) and hybrid search systems Skilled in deploying ML APIs using FastAPI or Flask Background in text-to-SQL applications or domain-specific LLMs Knowledge of ML Ops practices: model versioning, automated retraining, monitoring Familiarity with CI/CD for ML pipelines via Databricks Repos, GitHub Actions, etc. Contributions to open-source ML or GenAI projects Experience in the restaurant/hospitality tech or digital marketing domain Unleash Your Potential: What You Will Be Doing and Owning: Build and deploy GenAI-powered microservices and personalized recommendation engines Design and manage Databricks data pipelines for training, feature engineering, and inference Develop high-performance ML APIs and integrate with frontend applications Implement retrieval pipelines with vector DBs and search engines Define and maintain ML Ops workflows for versioning, retraining, and monitoring Drive strategic architectural decisions for LLM-powered, multi-model systems Collaborate across product and engineering teams to embed intelligence in customer experiences Enable CI/CD for ML systems with modern orchestration tools Advocate for scalability, performance, and clean code in all deployed solutions Interview Process: Interview #1: Phone Screen with Talent Acquisition Team Interview #2: Technical Interview – Round 1 with AI/ML Team (via MS Teams / F2F) Interview #3: Technical Interview – Round 2 with AI/ML Team (via MS Teams / F2F) Interview #4: Final Round with Hiring Manager and Cross-functional Stakeholders (via MS Teams / F2F PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.

For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram. Position Description We are seeking a Machine Learning Engineer to join our growing AI team at PAR . This role will focus on developing and scaling GenAI-powered services, recommender systems, and ML infrastructure that fuel personalized customer engagement. You will work across teams to drive technical excellence and real-world ML application impact. Position Location: Jaipur / Gurgaon Reports To [Hiring Manager Title – e.g., Head of AI or Senior Director, AI Engineering] Entrees (Requirements) What We’re Looking For: Master’s or PhD in Computer Science, Machine Learning, or a related field 3+ years of experience delivering production-ready machine learning solutions Deep understanding of ML algorithms, recommender systems, and NLP Experience with LLM frameworks (Hugging Face Transformers, LangChain, OpenAI API, Cohere) Strong proficiency in Python, including object-oriented design and scalable architecture Advanced expertise in Databricks: notebooks, MLflow tracking, data pipelines, job orchestration Hands-on experience with cloud-native technologies – preferably AWS (S3, Lambda, ECS/EKS, SageMaker) Experience working with modern data platforms: Delta Lake, Redis, Elasticsearch, NoSQL, BigQuery Strong verbal and written communication skills to translate technical work into business impact Flexibility to collaborate with global teams in PST/EST time zones when required With a Side Of (Additional Skills) Familiarity with vector databases (FAISS, ChromaDB, Pinecone, Weaviate) Experience with retrieval-augmented generation (RAG) and hybrid search systems Skilled in deploying ML APIs using FastAPI or Flask Background in text-to-SQL applications or domain-specific LLMs Knowledge of ML Ops practices: model versioning, automated retraining, monitoring Familiarity with CI/CD for ML pipelines via Databricks Repos, GitHub Actions, etc. Contributions to open-source ML or GenAI projects Experience in the restaurant/hospitality tech or digital marketing domain Unleash Your Potential: What You Will Be Doing and Owning: Build and deploy GenAI-powered microservices and personalized recommendation engines Design and manage Databricks data pipelines for training, feature engineering, and inference Develop high-performance ML APIs and integrate with frontend applications Implement retrieval pipelines with vector DBs and search engines Define and maintain ML Ops workflows for versioning, retraining, and monitoring Drive strategic architectural decisions for LLM-powered, multi-model systems Collaborate across product and engineering teams to embed intelligence in customer experiences Enable CI/CD for ML systems with modern orchestration tools Advocate for scalability, performance, and clean code in all deployed solutions Interview Process Interview #1: Phone Screen with Talent Acquisition Team Interview #2: Technical Interview – Round 1 with AI/ML Team (via MS Teams / F2F) Interview #3: Technical Interview – Round 2 with AI/ML Team (via MS Teams / F2F) Interview #4: Final Round with Hiring Manager and Cross-functional Stakeholders (via MS Teams / F2F PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.

We are seeking a visionary AI Architect to lead the design and integration of cutting-edge AI systems, including Generative AI , Large Language Models (LLMs) , multi-agent orchestration , and retrieval-augmented generation (RAG) frameworks. This role demands a strong technical foundation in machine learning, deep learning, and AI infrastructure, along with hands-on experience in building scalable, production-grade AI systems on the cloud. The ideal candidate combines architectural leadership with hands-on proficiency in modern AI frameworks, and can translate complex business goals into innovative, AI-driven technical solutions. Primary Stack & Tools: Languages : Python, SQL, Bash ML/AI Frameworks : PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers GenAI & LLM Tooling : OpenAI APIs, LangChain, LlamaIndex, Cohere, Claude, Azure OpenAI Agentic & Multi-Agent Frameworks : LangGraph, CrewAI, Agno, AutoGen Search & Retrieval : FAISS, Pinecone, Weaviate, Elasticsearch Cloud Platforms : AWS, GCP, Azure (preferred: Vertex AI, SageMaker, Bedrock) MLOps & DevOps : MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines, Terraform, FAST API Data Tools : Snowflake, BigQuery, Spark, Airflow Key Responsibilities: Architect scalable and secure AI systems leveraging LLMs , GenAI , and multi-agent frameworks to support diverse enterprise use cases (e.g., automation, personalization, intelligent search). Design and oversee implementation of retrieval-augmented generation (RAG) pipelines integrating vector databases, LLMs, and proprietary knowledge bases. Build robust agentic workflows using tools like LangGraph , CrewAI , or Agno , enabling autonomous task execution, planning, memory, and tool use. Collaborate with product, engineering, and data teams to translate business requirements into architectural blueprints and technical roadmaps. Define and enforce AI/ML infrastructure best practices , including security, scalability, observability, and model governance. Manage technical road-map, sprint cadence, and 3–5 AI engineers; coach on best practices. Lead AI solution design reviews and ensure alignment with compliance, ethics, and responsible AI standards. Evaluate emerging GenAI & agentic tools; run proofs-of-concept and guide build-vs-buy decisions. Qualifications: 10+ years of experience in AI/ML engineering or data science, with 3+ years in AI architecture or system design. Proven experience designing and deploying LLM-based solutions at scale, including fine-tuning , prompt engineering , and RAG-based systems . Strong understanding of agentic AI design principles , multi-agent orchestration , and tool-augmented LLMs . Proficiency with cloud-native ML/AI services and infrastructure design across AWS, GCP, or Azure. Deep expertise in model lifecycle management, MLOps, and deployment workflows (batch, real-time, streaming). Familiarity with data governance , AI ethics , and security considerations in production-grade systems. Excellent communication and leadership skills, with the ability to influence technical and business stakeholders.

SLSQ126R545 As an Enterprise Account Executive at Databricks, you are a sales professional experienced in leading go-to-market campaigns in one of the largest Banking institutions in India. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in depth and are passionate about communicating value to Customers and System Integrators. Databricks operates at the leading edge of the Unified Data Analytics and AI space. Our customers turn to us to lead the accelerated innovation that their businesses need to gain a first mover advantage in today’s ultra-competitive landscape. As we continue our rapid expansion, we are looking for a creative, execution-oriented Enterprise Account Executive to join the Retail & CPG team and maximize the phenomenal market opportunity that exists for Databricks. Reporting to our Director of Enterprise Sales, you will manage a strategic enterprise client in the BFSI vertical. Your informed perspective on Big Data, Advanced Analytics, and AI will help guide your successful execution strategy and allow you to provide genuine value to the client. The Impact You Will Have Present a territory plan within the first 90 days Meet with CIOs, IT executives, LOB executives, Program Managers, and other important partners Close both new accounts and existing accounts Identify and close quick, small wins while managing longer, complex sales cycles Exceed activity, pipeline, and revenue targets Track all customer details, including use case, purchase time frames, next steps, and forecasting in Salesforce Use a solution-based approach to selling and creating value for customers Promote Databricks' enterprise cloud data platform powered by Apache Spark Ensure 100% satisfaction among all customers Prioritize opportunities and apply appropriate resources Build a plan for success internally at Databricks and externally with your accounts What We Look For Previous field sales experience within big data, Cloud, SaaS, and a consumption selling motion Prior customer relationships with CIOs, program managers, and essential decision makers at local accounts The ability to simplify a technical capability into a value-based benefit 7+ years of Enterprise Sales experience exceeding quotas in BFSI accounts like ICICI Bachelor's Degree About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

SLSQ126R458 As an Enterprise Account Executive at Databricks, you are a sales professional experienced in leading go-to-market campaigns in a few of the largest Indian conglomerates. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in depth and are passionate about communicating value to Customers and System Integrators. Databricks operates at the cutting edge of the Unified Data Analytics and AI space. Our customers turn to us to lead the accelerated innovation that their businesses need to gain a first-mover advantage in today’s ultra-competitive landscape. As we continue our rapid expansion, we are looking for a creative, execution-oriented Enterprise Account Executive to join us and maximize the phenomenal market opportunity that exists for Databricks. Reporting to our Director of Enterprise Sales, you will manage a strategic enterprise vertical. Your informed perspective on Big Data, Advanced Analytics, and AI will help guide your successful execution strategy and allow you to provide genuine value to the client. The Impact You Will Have Present a territory plan within the first 90 days Meet with CIOs, IT executives, LOB executives, Program Managers, and other important partners Close both new accounts and existing accounts Identify and close quick, small wins while managing longer, complex sales cycles Exceed activity, pipeline, and revenue targets Track all customer details, including use case, purchase time frames, next steps, and forecasting in Salesforce Use a solution-based approach to selling and creating value for customers Promote Databricks' enterprise cloud data platform powered by Apache Spark Ensure 100% satisfaction among all customers Prioritize opportunities and apply appropriate resources Build a plan for success internally at Databricks and externally with your accounts. What We Look For Previous field sales experience within big data, Cloud, SaaS, and a consumption selling motion Prior customer relationships with CIOs, program managers, and essential decision makers at local accounts The ability to simplify a technical capability into a value-based benefit 7+ years of Enterprise Sales experience exceeding quotas in larger accounts (preferably with Indian conglomerate like Reliance.) Managing a small set of enterprise accounts rather than a broad territory Bachelor's Degree About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

computer vision or deep learning roles industrial/safety inspection datasets (e.g., PPE detection, visual defect classification). Familiarity with MLOps tools like MLflow, DVC, or ClearML. ONNX, TensorRT, OpenVINO

Hi, Please check the below role and let me know if you are interested. Share me your updated resume Position: Data Engineer Work Location: Kochi, Coimbatore, Chennai Work Type: Hybrid Onsite, 3 days onsite every week Experience-3+ Skills & Responsibilities: Data Engineering & Processing: Develop scalable data pipelines using Python and PySpark in Azure Databricks Work on data ingestion, cleansing, transformation, and preparation for analytics. Databricks & Azure Platform Skills: Hands-on experience with Databricks notebooks, Delta Lake, and working with structured and semi- structured data; MLFlow, use Azure Data Factory, Azure Data Lake, Azure SQL, and Cosmos DB for data processing and storage. Programming Skills: Strong proficiency in Python for data manipulation, automation, and orchestration tasks; familiarity with PySpark for distributed processing of large datasets. CI/CD & DevOps: Use Azure DevOps for version control, automated testing, and pipeline-based deployments; follow coding standards and peer review processes. Testing & Quality: Write and execute unit and validation tests for data pipelines; monitor job performance and troubleshoot data quality issues. Agile Collaboration: Participate in Agile ceremonies including stand-ups, sprint planning, and retrospectives; work closely with BAs, QAs, and architects to deliver high-quality solutions. Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Job Type: Contractual / Temporary Contract length: 12 months Pay: ₹800,000.00 - ₹1,800,000.00 per year Schedule: Day shift Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Preferred) Location: Chennai, Tamil Nadu (Required) Work Location: In person

Company Description About Sutherland Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise. We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence. We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model. For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland Unlocking digital performance. Delivering measurable results. Job Description We are looking for a proactive and detail-oriented AI OPS Engineer to support the deployment, monitoring, and maintenance of AI/ML models in production. Reporting to the AI Developer, this role will focus on MLOps practices including model versioning, CI/CD, observability, and performance optimization in cloud and hybrid environments. Key Responsibilities: Build and manage CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker. Monitor model performance and health using observability tools and dashboards. Ensure automated retraining, version control, rollback strategies, and audit logging for production models. Support deployment of LLMs, RAG pipelines, and agentic AI systems in scalable, containerized environments. Collaborate with AI Developers and Architects to ensure reliable and secure integration of models into enterprise systems. Troubleshoot runtime issues, latency, and accuracy drift in model predictions and APIs. Contribute to infrastructure automation using Terraform, Docker, Kubernetes, or similar technologies. Qualifications Required Qualifications: 3–5 years of experience in DevOps, MLOps, or platform engineering roles with exposure to AI/ML workflows. Hands-on experience with deployment tools like Jenkins, Argo, GitHub Actions, or Azure DevOps. Strong scripting skills (Python, Bash) and familiarity with cloud environments (AWS, Azure, GCP). Understanding of containerization, service orchestration, and monitoring tools (Prometheus, Grafana, ELK). Bachelor’s degree in computer science, IT, or a related field. Preferred Skills: Experience supporting GenAI or LLM applications in production. Familiarity with vector databases, model registries, and feature stores. Exposure to security and compliance standards in model lifecycle management

Responsibilities and Duties: Strategic Leadership (10%): Champion the AI/ML roadmap, driving strategic planning and execution for all initiatives. Provide guidance on data science projects (Agentic AI, Generative AI, and Machine Learning), aligning them with business objectives and best practices. Foster a data-driven culture, advocating for AI-powered solutions to business challenges and efficiency improvements. Collaborate with product management, engineering, and business stakeholders to identify opportunities and deliver impactful solutions Technical Leadership (40%): Architect and develop Proof-of-Concept (POC) solutions for Agentic AI, Generative AI, and ML. Utilize Python and relevant data science libraries, leveraging MLflow. Provide technical guidance on AI projects, ensuring alignment with business objectives and best practices. Assist in development and documentation of standards for ethical and regulatory-compliant AI usage. Stay current with AI advancements, contributing to the team's knowledge and expertise. Perform hands-on data wrangling and AI model development Operational Leadership (50%): Drive continuous improvement through Agentic AI, Generative AI, and predictive modeling. Participate in Agile development processes (Scrum and Kanban). Ensure compliance with regulatory and ethical AI standards. Other duties as assigned Required Abilities and Skills: Agentic AI development and deployment. Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Working with large datasets on AWS and Databricks Strong hands-on experience with: Agentic AI development and deployment. Working with large datasets on AWS and Databricks. Desired Experience: Statistical modeling, machine learning algorithms, and data mining techniques. Databricks and MLflow for model training, deployment, and management on AWS. Experience integrating AI with IoT/event data. Experience with real-time and batch inference integration with SaaS applications. International team management experience. Track record of successful product launches in regulated environments Education and Experience: 5+ years of data science/AI experience Bachelor's degree in Statistics, Data Science, Computer Engineering, Mathematics, or a related field (Master's preferred). Proven track record of deploying successful Agentic AI, Generative AI, and ML projects from concept to production. Excellent communication skills, able to explain complex technical concepts to both technical and non-technical audiences.

Roles & Responsibilities Qualifications and Skills: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field. 5+ years of hands-on experience in data science or machine learning roles. Strong proficiency in Python or R, with deep knowledge of libraries like scikit-learn, pandas, NumPy, TensorFlow, or PyTorch. Proficient in SQL and working with relational databases. Solid experience with Azure cloud platforms and data pipeline tools. Strong grasp of statistical methods, machine learning algorithms, and model evaluation techniques. Excellent communication and storytelling skills with the ability to influence stakeholders. Proven track record of delivering impactful data science solutions in a business setting. Preferred Qualifications Experience working in industries such as [logistics, aerospace, marketing, etc.]. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Knowledge of data visualization tools (e.g., Tableau, Power BI, Plotly). Responsibilities And Duties Model Development: Design, build, and deploy scalable machine learning models to solve key business challenges (e.g., customer churn, recommendation engines, pricing optimization). Data Analysis: Perform exploratory data analysis (EDA), statistical testing, and feature engineering to uncover trends and actionable insights. Project Leadership: Lead end-to-end data science projects, including problem definition, data acquisition, modeling, and presentation of results to stakeholders. Cross-functional Collaboration: Partner with engineering, product, marketing, and business teams to integrate models into products and processes. Mentorship: Guide and mentor junior data scientists and analysts, helping them grow technically and professionally. Innovation: Stay current with the latest data science techniques, tools, and best practices. Evaluate and incorporate new technologies when appropriate. Communication: Translate complex analyses and findings into clear, compelling narratives for non-technical stakeholders. Experience 8-11 Years Skills Primary Skill: Data Science Sub Skill(s): Data Science Additional Skill(s): Data Science

Vayuz Technologies is seeking an innovative and self-starting Artificial Intelligence Engineer. You will be an AI expert with a strong background in making architectural tradeoffs to optimize AI performance for a variety of use cases. This role involves close collaboration with internal and external development engineers (architecture, hardware, validation, software services), contributing to development, and supporting device characterization and benchmarking efforts. Responsibilities Large Models & Deep Neural Networks: Demonstrate proficiency and hands-on experience in working with large models and deep neural networks. LLM Expertise: Possess expertise in LLMs with working knowledge of large language models (LLMs). System Architecture: Bring extensive experience in System platform Architecture. Development Experience: Experience in development, preferably for memory/storage/any embedded system. Standards & Patents: Possess in-depth knowledge and extensive experience in dealing with Standardizations, Technical Papers, and Patents. Programming Proficiency: Extensive experience with C/C++ and Python programming. LLM Development & Fine-tuning: Develop and fine-tune LLMs (e.g., GPT, Llama, Mistral, Falcon, Claude) for domain-specific applications. RAG Pipeline Implementation: Implement RAG (Retrieval Augmented Generation) pipelines using tools like LlamaIndex, LangGraph, and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to significantly enhance response accuracy. AI-Powered Agents: Build advanced AI-powered chatbots and autonomous agents using frameworks like LangGraph, CrewAI, and leveraging LlamaIndex and OpenAI APIs. Generative AI Optimization & Deployment: Optimize and deploy generative AI models for real-time inference using cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools (e.g., Docker, Kubernetes, MLflow). Model Fine-tuning Techniques: Fine-tune models using techniques such as LoRA, QLoRA, PEFT, and RLHF to improve efficiency and personalization. AI-Driven Workflows: Develop AI-driven workflows for structured reasoning and decision-making using CrewAI and LangGraph. Multi-Modal AI Integration: Integrate multi-modal AI models (text, image, speech) into comprehensive enterprise solutions. Memory & Retrieval Strategies: Implement memory and retrieval strategies for LLM-based systems using vector search and caching techniques. Ethical AI: Ensure AI models adhere to ethical AI guidelines, incorporate bias mitigation strategies, and follow robust security best practices. Requirements B.Tech in Computer Science or Electrical Engineering. Experience in the relevant domain. Strong analytical and abstract thinking ability, as well as excellent technical communication skills. Able to work independently and perform effectively in a fast-paced environment. Ability to troubleshoot and debug complex issues efficiently. Working knowledge of Device Drivers is desirable. Prior experience in working with Agile/Scrum methodologies. Required Skills Languages & Frameworks: Proficiency in Python, PyTorch, TensorFlow, JAX. LLMs: Large Language Models (GPT, Llama, Mistral, Falcon, Claude). Vector Databases: FAISS, Pinecone, Weaviate, ChromaDB. AI Frameworks: LlamaIndex, LangGraph, CrewAI, OpenAI APIs. MLOps & Cloud: Docker, Kubernetes, MLflow, AWS, GCP, Azure. Fine-tuning: LoRA, QLoRA, PEFT, RLHF.

The role of Data Scientist - Clinical Data Extraction & AI Integration in our healthcare technology team requires an experienced individual with 3-6 years of experience. As a Data Scientist in this role, you will be primarily focused on medical document processing and data extraction systems. You will have the opportunity to work with advanced AI technologies to create solutions that enhance the extraction of crucial information from clinical documents, thereby improving healthcare data workflows and patient care outcomes. Your key responsibilities will include designing and implementing statistical models for medical data quality assessment, developing predictive algorithms for encounter classification, and validation. You will also be responsible for building machine learning pipelines for document pattern recognition, creating data-driven insights from clinical document structures, and implementing feature engineering for medical terminology extraction. Furthermore, you will apply natural language processing (NLP) techniques to clinical text, develop statistical validation frameworks for extracted medical data, and build anomaly detection systems for medical document processing. Additionally, you will create predictive models for discharge date estimation, encounter duration, and implement clustering algorithms for provider and encounter classification. In terms of AI & LLM Integration, you will be expected to integrate and optimize Large Language Models via AWS Bedrock and API services, design and refine AI prompts for clinical content extraction with high accuracy, and implement fallback logic and error handling for AI-powered extraction systems. You will also develop pattern matching algorithms for medical terminology and create validation layers for AI-extracted medical information. Having expertise in the healthcare domain is crucial for this role. You will work closely with medical document structures, implement healthcare-specific validation rules, handle medical terminology extraction, and conduct clinical context analysis. Ensuring HIPAA compliance and adhering to data security best practices will also be part of your responsibilities. Proficiency in programming languages such as Python 3.8+, R, SQL, and JSON, along with familiarity with data science tools like pandas, numpy, scipy, scikit-learn, spaCy, and NLTK is required. Experience with ML Frameworks including TensorFlow, PyTorch, transformers, huggingface, and visualization tools like matplotlib, seaborn, plotly, Tableau, and PowerBI is desirable. Knowledge of AI Platforms such as AWS Bedrock, Anthropic Claude, OpenAI APIs, and experience with cloud services like AWS (SageMaker, S3, Lambda, Bedrock) will be advantageous. Familiarity with research tools like Jupyter notebooks, Git, Docker, and MLflow is also beneficial for this role.,

Additional Locations: India-Haryana, Gurgaon Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. Senior Software Engineer-MLOps We are looking for a highly skilled Senior Software Engineer – MLOps with deep expertise in building and managing production-grade ML pipelines in AWS and Azure cloud environments. This role requires a strong foundation in software engineering, DevOps principles, and ML model lifecycle automation to enable reliable and scalable machine learning operations across the organization Key Responsibilities include: Design and build robust MLOps pipelines for model training, validation, deployment, and monitoring Automate workflows using CI/CD tools such as GitLab Actions, Azure DevOps, Jenkins, or Argo Workflows Build and manage ML workloads on AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena) and Azure (Azure ML Foundry, AKS, ADF, Blob Storage) Design secure and cost-efficient ML architecture leveraging cloud-native services Manage infrastructure using IaC tools such as Terraform, Bicep, or CloudFormation Implement cost optimization and performance tuning for cloud workloads Package ML models using Docker, and orchestrate deployments with Kubernetes on EKS/AKS Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Integrate observability tools for model performance, drift detection, and lineage tracking (e.g., Fiddler, MLflow, Prometheus, Grafana, Azure Monitor, CloudWatch) Ensure model reproducibility, versioning, and compliance with audit and regulatory requirements Collaborate with data scientists, software engineers, DevOps, and cloud architects to operationalize AI/ML use cases Mentor junior MLOps engineers and evangelize MLOps best practices across teams Required Qualification: Bachelor's/Master’s in Computer Science, Engineering, or related discipline 10 years in Devops, with 2+ years in MLOps. Proficient with MLflow, Airflow, FastAPI, Docker, Kubernetes, and Git. Experience with feature stores (e.g., Feast), model registries, and experiment tracking. Proficiency in Devops & MLOps, Automation Cloud formation/Teraform/BICEP Requisition ID: 610750 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

Additional Locations: India-Haryana, Gurgaon Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. Software Engineer-MLOps We are seeking an enthusiastic and detail-oriented MLOps Engineer to support the development, deployment, and monitoring of machine learning models in production environments. This is a hands-on role ideal for candidates looking to grow their skills at the intersection of data science, software engineering, and DevOps. You will work closely with senior MLOps engineers, data scientists, and software developers to build scalable, reliable, and automated ML workflows across cloud platforms like AWS and Azure Key Responsibilities include: Assist in building and maintaining ML pipelines for data preparation, training, testing, and deployment Support the automation of model lifecycle tasks including versioning, packaging, and monitoring Build and manage ML workloads on AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena) and Azure (Azure ML Foundry, AKS, ADF, Blob Storage) Assist with containerizing ML models using Docker, and deploying using Kubernetes or cloud-native orchestrators Manage infrastructure using IaC tools such as Terraform, Bicep, or CloudFormation Participate in implementing CI/CD pipelines for ML workflows using GitHub Actions, Azure DevOps, or Jenkins Contribute to testing frameworks for ML models and data validation (e.g., pytest, Great Expectations). Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation Participate in diagnosing issues related to model accuracy, latency, or infrastructure bottlenecks Continuously improve knowledge of MLOps tools, ML frameworks, and cloud practices. Required Qualification: Bachelor's/Master’s in Computer Science, Engineering, or related discipline 7 years in Devops, with 2+ years in MLOps. Good Understanding of MLflow, Airflow, FastAPI, Docker, Kubernetes, and Git. Proficient in Python and familiar with bash scripting Exposure to MLOps platforms or tools such as SageMaker Studio, Azure ML, or GCP Vertex AI. Requisition ID: 610751 As a leader in medical science for more than 40 years, we are committed to solving the challenges that matter most – united by a deep caring for human life. Our mission to advance science for life is about transforming lives through innovative medical solutions that improve patient lives, create value for our customers, and support our employees and the communities in which we operate. Now more than ever, we have a responsibility to apply those values to everything we do – as a global business and as a global corporate citizen. So, choosing a career with Boston Scientific (NYSE: BSX) isn’t just business, it’s personal. And if you’re a natural problem-solver with the imagination, determination, and spirit to make a meaningful difference to people worldwide, we encourage you to apply and look forward to connecting with you!

Job Information Date Opened 07/25/2025 Job Type Permanent RSD NO 11513 Industry IT Services Min Experience 5 Max Experience 7 City Chennai State/Province Tamil Nadu Country India Zip/Postal Code 600018 Job Description Data Scientist – Retail/CPG Domain Are you a data-driven problem solver with a passion for Retail and CPG analytics? We’re looking for a contract-based Data Scientist to join our team and deliver high-impact insights that drive business decisions. What You’ll Work On: Category & Product Analytics – Product assortment, category performance, and new product launches Sales Data Analysis – Sales trends, forecasting, and identifying key drivers Customer Analytics – Loyalty data and campaign effectiveness (good to have) Key Skills: Advanced data analysis and ML model development Experience with CI/CD pipelines for ML workflows (MLflow, Azure ML) Strong in Python, SQL, Databricks; PySpark is a plus Power BI experience is a plus for building impactful dashboards and visualizations Ability to translate insights into compelling stories for senior stakeholders Deep understanding of Retail and FMCG domain challenges Experience Required: 5–7 years in analytics Location: Bangalore / Chennai At Indium diversity, equity, and inclusion (DEI) are the cornerstones of our values. We champion DEI through a dedicated council, expert sessions, and tailored training programs, ensuring an inclusive workplace for all. Our initiatives, including the WE@IN women empowerment program and our DEI calendar, foster a culture of respect and belonging. Recognized with the Human Capital Award, we are committed to creating an environment where every individual thrives. Join us in building a workplace that values diversity and drives innovation.

As a Data Scientist for AI Products at Linde, you will be an integral part of the Artificial Intelligence team within Linde's global corporate division. Your primary responsibility will involve working on real business challenges and opportunities across multiple countries. Your focus will be on supporting the AI team in extending existing AI products and developing new ones to cater to various use cases within Linde's business and value chain. Collaboration with diverse teams including Project Managers, Data Scientists, Data and Software Engineers will be a key aspect of your role. You will directly work with a variety of data sources, types, and structures to derive actionable insights. Developing, customizing, and managing AI software products based on Machine and Deep Learning backends will be among your core tasks. Your role will also entail supporting the replication of existing products and pipelines to other systems and geographies, defining data requirements for new developments, and interacting with business functions to identify opportunities with potential business impact. To excel in this role, you are required to have a Bachelor's or Master's degree in data science, Computational Statistics/Mathematics, Computer Science, Operations Research, or a related field. A strong understanding and practical experience in Multivariate Statistics, Machine Learning, and Probability concepts are essential. Additionally, hands-on experience with preprocessing, feature engineering, data cleansing, and Python programming skills are crucial. Proficiency in handling large datasets using SQL, knowledge of data architectures, and experience with data visualization tools like Tableau or PowerBI are desired. Your result-driven mindset, excellent communication skills, and ability to structure projects from ideation to implementation will be valuable assets in this role. Fluency in English is a must, and any experience with DevOps, MS Azure, Azure ML, Kedro, Airflow, MLflow, or similar tools will be advantageous. Working at Linde offers you the opportunity to be part of a leading global industrial gases and engineering company with a strong commitment to sustainable development and customer success. If you are looking for a challenging yet rewarding career where you can make a positive impact on the world, Linde provides limitless possibilities for your professional growth. Join us in our mission to make the world more productive and sustainable. Let's talk about how you can contribute to our team!,