531 Mlops Jobs - Page 19

We are seeking a skilled and experienced Machine Learning Engineer to join our team.The ideal candidate will have a strong background in Python and PyTorch, along with 4-8 years of experience deploying ML/AI models to production. This role requires excellent analytics skills and a good working knowledge of Databricks. You will work closely with data scientists, clinicians, software engineers, and product teams to design, build, and optimize scalable machine learning solutions. Role & responsibilities Develop, train, and optimize machine learning models using PyTorch and other ML frameworks. Deploy and maintain ML models in production environments, ensuring scalability, performance, and reliability. Utilize Databricks for data processing, model training, model deployment, and pipeline optimization. Deploy Retrieval-Augmented Generation (RAG) pipelines to production for improved AI-driven applications. Collaborate with data engineers to design and implement ETL workflows and data pipelines. Perform rigorous testing, validation, and monitoring of deployed models. Optimize model inference for low latency and high throughput applications. Work with stakeholders to translate business problems into ML solutions. Stay up to date with the latest advancements in machine learning, deep learning, and AI deployment strategies. Preferred candidate profile Proficiency in Python and ML frameworks such as PyTorch. 4-8 years of experience deploying machine learning models to production. Knowledge of MLflow for experiment tracking and model management. Strong experience with Databricks for ML development and deployment. Hands-on experience with MLOps, CI/CD pipelines, and cloud-based deployment (AWS, Azure, or GCP). Solid understanding of data structures, algorithms, and software engineering principles. Experience working with large-scale datasets and distributed computing frameworks. Experience with deploying Retrieval-Augmented Generation (RAG) pipelines to production. Excellent analytical and problem-solving skills. Strong communication skills and ability to work in a collaborative team environment. Preferred Qualifications Experience deploying models in the healthcare domain. Experience with feature engineering, data preprocessing, and model explainability. Knowledge of containerization (Docker, Kubernetes) and workflow orchestration tools Familiarity with LLMs, NLP, or reinforcement learning is a plus.

Role & responsibilities : Leadership & Strategy : Lead and manage a team of 20 Data Scientists (DS), ensuring high performance and continuous growth Define and implement the companys data science vision and strategy Work closely with global business leaders to identify opportunities where data science can drive business value Stay up to date with emerging trends in AI, ML, and advanced data analytics to drive innovation. Ensure all agreed Key Performance Indicators (KPIs) are met in line with performance agreements, maintaining high standards of operational efficiency Data Science : Develop and deploy machine learning models, statistical algorithms and predictive analytics solutions. Ensure the scalability, reliability and efficiency of data science models and pipelines. Collaborate with engineering and data teams to improve data quality, availability and infrastructure Participate in global meets & workshops to review & develop strong process and strategy for DS services in India Utilize advanced analytics to solve complex business problems and improve decision-making Stakeholder Management : Partner with cross-functional teams (engineering, operations) to translate business needs into data-driven solutions Communicate insights and recommendations to both technical and non-technical stakeholders Develop data-driven strategies to optimize customer experience, revenue and operational efficiency Exhibit very strong local and global stakeholders management skill Support in developing proactive proposals and solutions to internal and external stakeholders. Team Development & Mentorship : Recruit, train and mentor Data Scientists, Data Engineers and AI platform engineers, fostering a culture of innovation. Support HR partner with building hiring strategy for the niched skills Conduct performance evaluations, provide feedback and set career development plans for the team members Encourage best practices in coding, model deployment and data governance. Desired candidate profile : Bachelors or Masters or PhD in Data Science, Computer Science, Statistics, Mathematics or a related field. Technical Skills: 10-15 years of total experience with min 5 yrs in data science, analytics, AI/Deep Learning, NLP and Generative AI . Strong proficiency in Python, R, SQL and cloud platforms ( AWS, GCP, or Azure ) Expertise in Machine Learning frameworks ( TensorFlow, PyTorch, Scikit-learn ) Experience with big data technologies (Spark, Hadoop, Databricks) and data engineering concepts. Solid understanding of statistics, probability and optimization techniques. Experience with MLOps, model deployment and productionizing ML models . Industry experience in Aviation, Automotive, Finance, Healthcare, Retail or any IT Technology based domain. Leadership & Business Acumen : • Proven experience in leading and managing data science teams. • Ability to translate business problems into data science solutions. • Strong communication and stakeholder management skills. • Experience in budget planning, resource allocation and project management. • Proficiency in Risk assessment and mitigation planning.

AI Ops Senior Architect 12 -17 Years Work Location - Pune/ Bengaluru/Hyderabad/Chennai/ Gurugram Tredence is Data science, engineering, and analytics consulting company that partners with some of the leading global Retail, CPG, Industrial and Telecom companies. We deliver business impact by enabling last mile adoption of insights by uniting our strengths in business analytics, data science and data engineering. Headquartered in the San Francisco Bay Area, we partner with clients in US, Canada, and Europe. Bangalore is our largest Centre of Excellence with skilled analytics and technology teams serving our growing base of Fortune 500 clients. JOB DESCRIPTION At Tredence, you will lead the evolution of Industrializing AI ” solutions for our clients by implementing ML/LLM/GenAI & Agent Ops best practices. You will lead the Architecture , Design & development of large scale ML/LLMOps platforms for our clients. You’ll build and maintain tools for deployment, monitoring, and operations. You’ll be a trusted advisor to our clients in ML/GenAI/Agent Ops space & coach to the ML engineering practitioners to build effective solutions to Industrialize AI solutions THE IDEAL CANDIDATE WILL BE RESPONSIBLE FOR AI Ops Strategy, Innovation, Research and Technical Standards 1. Conduct research and experiment with emerging AI Ops technologies and trends. Create POV’s, POC’s & present Proof of Technology to use latest tools, Technologies & services from Hyper scalers focussed on ML, GenAI & Agent Ops 2. Define and propose new technical standards and best practices for the organization's AI Ops environment. 3. Lead the evaluation and adoption of innovative MLOps solutions to address critical business challenges. 4. Conduct meet ups, attend & present in Industry events, conferences, etc 5. Ideate & develop accelerators to strengthen service offerings of AI Ops practice Solution Design & Architectural Development 6. Lead Design & architecture of scalable model training & deployment pipelines for large-scale deployments 7. Architect & Design large scale ML & GenAI Ops platforms 8. Collaborate with Data science & GenAI practice to define and implement strategies of AI solutions for model explainability and interpretability 9. Mentor and guide senior architects in crafting cutting-edge AI Ops solutions 10. Lead architecture reviews and identify opportunities for significant optimizations and improvements. Documentation and Best Practices 11. Develop and maintain comprehensive documentation of AIOps architectures designs and best practices. 12. Lead the development and delivery of training materials and workshops on AIOps tools and techniques. 13. Actively participate in sharing knowledge and expertise with the MLOps team through internal presentations and code reviews. Qualifications and Skills: 1. Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field with minimum 12 years of experience 2. Proven experience in architecting & developing AIOps solutions – to streamline Machine Learning & GenAI development lifecycle 3. Proven experience as an AI Ops Architect – ML & GenAI in architecting & design of ML & GenAI platforms 4. Hands on experience in Model deployment strategies, Designing ML & GenAI model pipelines to scale in production, Model Observability techniques used to monitor performance of ML & LLM’s 5. Strong coding skills with experience in implementing best coding practices Technical Skills & Expertise Python, PySpark, PyTorch ,Java, Micro Services, API’s LLMOps – Vector DB, RAG, LLM Orchestration tools, LLM Observability, LLM Guardrails, Responsible AI MLOps - MLFlow, ML/DL libraries, Model & Data Drift Detection libraries & techniques Real Time & Batch Streaming Container Orchestration Platforms Cloud platforms – Azure/ AWS/ GCP, Data Platforms – Databricks/ Snowflake Nice to Have: Understanding of Agent Ops Exposure to Databricks platform You can expect to – Work with world’s biggest Retailers, CPG’s, HealthCare, Banking & Manufacturing customers and help them solve some of their most critical problems Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices. Work in a diverse environment that keeps evolving Hone your entrepreneurial skills as you contribute to growth of the organization

We are seeking a skilled Back End Developer with a focus on NodeJS to join our dynamic team. As a Back End Developer, you will be responsible for developing server-side logic, database integration, and ensuring high performance and responsiveness to requests from the front-end. We Eximietas Design About Eximietas History Careers Job Openings Connect Contact Us Engineer Silicon Silicon Design MicroArchitecture and RTL design Design Verification Physical Implementation Analog/Mixed Signal DFT Verification & Validation Presilicon Validation Post Silicon Validation Devices Embedded Software Firmware BSP & Drivers Multimedia Connectivity Edge AI Hardware Design Services High Speed Digital Design Hardware & Board Design Services Cloud & Digital Infrastructure & DevOps Secure Foundation Infrastructure as Code CI/CD Monitoring & Observability Modernization & Migration Workload Migration Application Development API & Application Integration Application Migration Modernize Applications Database Modernization Enterprise Database Migration Cyber Security Security Strategy & Compliance Identity & Access Management Infrastructure & Application Security Data Security & Privacy Threat Intelligence AI & Data Analytics AI & Machine Learning MLOps Conversational AI Generative AI Data Analytics Data Warehouse & Lake Modernization Business Intelligence & Data Visualization Excellence Why Eximietas Case Studies Blogs The Think Tank News and Events Click We Eximietas Design About Eximietas History Careers Job Openings Connect Contact Us Engineer Silicon Silicon Design MicroArchitecture and RTL design Design Verification Physical Implementation Analog/Mixed Signal DFT Verification & Validation Presilicon Validation Post Silicon Validation Devices Embedded Software Firmware BSP & Drivers Multimedia Connectivity Edge AI Hardware Design Services High Speed Digital Design Hardware & Board Design Services Cloud & Digital Infrastructure & DevOps Secure Foundation Infrastructure as Code CI/CD Monitoring & Observability Modernization & Migration Workload Migration Application Development API & Application Integration Application Migration Modernize Applications Database Modernization Enterprise Database Migration Cyber Security Security Strategy & Compliance Identity & Access Management Infrastructure & Application Security Data Security & Privacy Threat Intelligence AI & Data Analytics AI & Machine Learning MLOps Conversational AI Generative AI Data Analytics Data Warehouse & Lake Modernization Business Intelligence & Data Visualization Excellence Why Eximietas Case Studies Blogs The Think Tank News and Events Click Cloud / 3+ Years Back End Developer Bengaluru/Bhubaneswar Job Description We are seeking a skilled Back End Developer with a focus on NodeJS to join ourdynamic team. As a Back End Developer, you will be responsible for developing server-side logic, database integration, and ensuring high performance and responsiveness to requests from the front-end. You will collaborate with cross-functional teams to define, design, and ship new features and enhancements to our existing applications. The ideal candidate will have a strong understanding of Backend technologies, excellent problem-solving skills, and a passion for creating scalable and efficient systems. Responsibilities Design, develop, and maintain scalable, high-availability backend services using js. Develop RESTful APIs using js and Express to ensure seamless communication between the frontend and backend components. Integrate and manage databases, both relational (e.g., PostgreSQL) and/or NoSQL (e.g., MongoDB), to store, retrieve, and manipulate data Write clean, maintainable, and efficient code; perform code reviews to ensure code Implement thorough testing practices, including unit and integration testing, to maintain code quality and Requirements Bachelor s degree in computer science, Software Engineering, or a related 3+ years of professional experience as a Backend Developer, specializing in Strong command over js and Express for backend development. Solid experience with both SQL (e.g., PostgreSQL) and/or NoSQL (e.g., MongoDB) Familiarity with version control systems (e.g., Git) and agile development Excellent problem-solving skills and the ability to debug and troubleshoot complex technical Strong communication skills, both written and verbal, to collaborate effectively with technical and non-technical Strong experience with microservices architecture and system design. Preferred Qualifications Experience with cloud platforms such as AWS, Azure, or Google Cloud Knowledge of containerization technologies like Docker and orchestration tools such as Familiarity with continuous integration and continuous deployment (CI/CD) Understanding of Agile methodologies and DevOps

We are looking for experienced Senior and Principal Machine Learning Engineers across two teams: InstructLab and OpenShift AI . In this role, you will build, optimize, and scale machine learning models while contributing to innovative AI-driven solutions, and assisting users in understanding ML predictions. During the hiring process, we'll work with you to determine the best team placement based on your background and interests. While the core job requirements remain consistent, your day-to-day responsibilities will align with your chosen team's objectives. Successful applicants must reside in a country where Red Hat is registered to do business. What you will do Specific responsibilities will vary based on team placement, but may include: Design and implement machine learning systems Develop and optimize ML models for production use Create and maintain ML infrastructure and pipelines Ensure ML systems are scalable and maintainable Collaborate with data scientists to productionize models Collaborate closely with researchers, software developers, and upstream AI/ML communities Mentor and guide other team members What you will bring Experience in AI development, deep learning, machine learning libraries (e.g. pytorch, scikit-learn), prompt engineering, and/or fundamental mathematics Experience in feature engineering Experience in Go or Python development Experience in Kubernetes, OpenShift, Docker, or other cloud-native technologies Experience in agile development, Jira, and Git Ability to quickly learn and use new tools and technologies Excellent written and verbal communication skills The following skills are valued and may influence team placement: Masters or PhD in Machine Learning (ML) or Natural Language Processing (NLP) Active participation in KServe, TrustyAI, Kubeflow, or other open source communities Specialized expertise in specific AI domains (NLP, Computer Vision, MLOps, etc.)

About Us: At Novus Loyalty, we are committed to building cutting-edge AI-driven solutions that enhance business performance and user experience. We are currently seeking a skilled and passionate AI Engineer to join our team, with a strong emphasis on Azure AI technologies. Key Responsibilities: Design, develop, and deploy AI models using Azure AI services. Work on various AI domains, including Generative AI, Agentic AI, and other advanced ML models. Collaborate with cross-functional teams to integrate AI solutions into production environments. Conduct data analysis and preprocessing to support model development. Monitor and optimize AI model performance and accuracy. Stay up-to-date with emerging AI technologies, tools, and best practices. Required Qualifications: Minimum 3 years of hands-on experience in AI/ML model development. Proven experience with Azure AI services (e.g., Azure Machine Learning, Cognitive Services, Azure OpenAI). Strong programming skills in Python or other relevant languages. Solid understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with large language models (LLMs), NLP, or generative AI applications is a plus. Familiarity with MLOps practices and cloud-based model deployment. Excellent problem-solving and communication skills.

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle

About this role: Wells Fargo is seeking a Software Engineer. In this role, you will: Participate in low to moderately complex initiatives and projects associated with the technology domain, including installation, upgrades, and deployment efforts Identify opportunities for service quality and availability improvements within the technology domain environment Design, code, test, debug, and document for low to moderately complex projects and programs associated with technology domain, including upgrades and deployments Review and analyze technical assignments or challenges that are related to low to medium risk deliverables and that require research, evaluation, and selection of alternative technology domains Present recommendations for resolving issues or may escalate issues as needed to meet established service level agreements Exercise some independent judgment while also developing understanding of given technology domain in reference to security and compliance requirements Provide information to technology colleagues, internal partners, and stakeholders Required Qualifications: 2+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Contribute to large scale planning of AI strategies and roadmaps Lead projects and act as an escalation point, provide guidance and direction to less experienced staff Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

About this role: Wells Fargo is seeking a Software Engineer. In this role, you will: Participate in low to moderately complex initiatives and projects associated with the technology domain, including installation, upgrades, and deployment efforts Identify opportunities for service quality and availability improvements within the technology domain environment Design, code, test, debug, and document for low to moderately complex projects and programs associated with technology domain, including upgrades and deployments Review and analyze technical assignments or challenges that are related to low to medium risk deliverables and that require research, evaluation, and selection of alternative technology domains Present recommendations for resolving issues or may escalate issues as needed to meet established service level agreements Exercise some independent judgment while also developing understanding of given technology domain in reference to security and compliance requirements Provide information to technology colleagues, internal partners, and stakeholders Required Qualifications: 2+ years of software engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Work as a Generative AI engineer developing enterprise-scale AI applications Design, implement, and optimize LLM-based solutions using state-of-the-art frameworks Lead Gen AI initiatives focused on developing intelligent agents and conversational systems Design and build robust LLM interfaces and orchestration pipelines Develop evaluation frameworks to measure and improve model performance Implement prompt engineering techniques to optimize model outputs Integrate Gen AI capabilities with existing enterprise applications Build and maintain frontend interfaces for AI applications Strong proficiency in Python/Java and LLM orchestration frameworks (LangChain, LangGraph) Basic Knowledge of model context protocols, RAG architectures, and embedding techniques Experience with model evaluation frameworks and metrics for LLM performance Proficiency in frontend development with React.js for AI applications Experience with UI/UX design patterns specific to AI interfaces Experience with vector databases and efficient retrieval methods Knowledge of prompt engineering techniques and best practices Experience with containerization and microservices architecture Strong understanding of semantic search and document retrieval systems Working knowledge of both structured and unstructured data processing Experience with version control using GitHub and CI/CD pipelines Experience working with globally distributed teams in Agile scrums Job Expectations: Understanding of enterprise use cases for Generative AI Knowledge of responsible AI practices and ethical considerations Ability to optimize AI solutions for performance and cost Well versed in MLOps concepts for LLM applications Staying current with rapidly evolving Gen AI technologies and best practices Experience implementing security best practices for AI applications

KEY RESPONSIBILITIES Proactively drive data science engineering projects forward with a self-motivated and go-getter attitude, effectively navigating ambiguity and managing at-times incomplete requirements. The Python data/ML engineer role is a hands-on software development role specializing in the development from scratch and delivery of data and machine learning based applications and POCs including generative AI based applications. The core emphasis of the role is on backend engineering and API development, with additional emphasis on data ingestion and data processing pipelines. Build on top of and utilize Azure Cloud or AWS platforms, leveraging familiarity with components such as IAM, storage, compute, services, and application development. Develop, maintain, and optimize Python code bases to ensure performance, readability, and adherence to code standards like PEP8, including implementing comprehensive test coverage. Design, develop, and deploy scalable and performant Python web services and APIs for diverse architectures, including synchronous and asynchronous REST APIs. Implement and maintain event-driven product architectures and batch processing systems to support scalable and efficient data processing. Develop and deploy LLM-based and GenAI applications using tools and frameworks such as OpenAI, HuggingFace Transformers, LlamaIndex, and vector stores/databases like Chroma, FAISS, Qdrant, and Weaviate Utilize the Elastic stack (Elastic, Logstash, Kibana) and Databricks for data processing and analytics as preferred Effectively use version control, containerization, CI/CD pipelines, and the deployment of applications on Azure using Git and Docker. Manage SQL databases, such as PostgreSQL, ensuring efficient backend operations and data integrity. Collaborate effectively with cross-functional teams, including data scientists, engineers, and architects, to build and release data and AI applications. Communicate clearly and effectively in English, facilitating interactions and collaboration within a globally distributed and diverse data science and engineering team.

Job Title : Engineering Manager Location : HSR Layout, Bangalore Employment Type : Full-Time Key Responsibilities : - Oversee the use of deep learning algorithms for a range of applications, such as CNNs, RNNs, and Transformers. - Effectively coordinate cross-functional teams while overseeing the AI project lifecycle from inception to delivery. - Lead the creation, advancement, and implementation of cutting-edge AI technologies, making sure they complement corporate objectives. - Mentor junior team members to foster growth and ensure quality deliverables. Requirements : - Proven experience in managing AI projects and leading technical teams. - Strong knowledge of deep learning architectures, particularly CNNs and Transformers. - Experience in team leadership, mentoring, and fostering a positive work culture. Technical Skills : - Experience in people management - Expertise in data processing, ML systems, MLOps, and infrastructure - 5+ years with cloud tech , DevOps/MLOps. - Strong skills in Python, SQL, and data modeling (DBT is a plus) - Familiar with Spark, Airflow, PyTorch, Scikit-learn, Pandas, Keras - Experience leading engineering teams in ML adoption Preferred Skills : - Strong project management skills, with experience in Agile methodologies. - Excellent communication and collaboration abilities across technical and non-technical teams. - Contributions to open-source AI projects or a portfolio demonstrating impactful work. What We Offer : - A chance to work on groundbreaking GenAI projects in a fast-paced startup environment. - A supportive and innovative team culture that encourages learning and collaboration.

Why Join? Above market-standard compensation Contract-based or freelance opportunities (212 months) Work with industry leaders solving real AI challenges Flexible work locations Remote | Onsite | Hyderabad/Bangalore Your Role: Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD) Automate ML workflows (feature engineering, retraining, deployment) Scale ML models with Docker, Kubernetes, Airflow Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure) Must-Have Skills: Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) Expertise in monitoring tools (MLflow, Prometheus, Grafana) Knowledge of distributed data processing (Spark, Kafka) (Bonus: Experience in A/B testing, canary deployments, serverless ML)

Your Responsibilities: Build & automate ML pipelines (Kubeflow, MLflow, Airflow) Develop & optimize CI/CD workflows Deploy ML models at scale with Docker, Kubernetes, cloud ML platforms Implement monitoring & governance frameworks Must-Have Skills: Python, TensorFlow, PyTorch AWS, GCP, Azure ML expertise CI/CD, monitoring, data versioning knowledge Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

We are looking for a seasoned Data Architect (Senior Engineer) to lead the design and implementation of scalable, secure, and privacy-compliant data architectures that support feedback-driven AI systems.

AI / ML Engineer Work Location: Remote Shift Timings: General Day Shift IST Time Zone Experience Required: 5+ Years Job Description: AI/ML resource with ML Ops Key Skills: • 3+ years of experience in AI/ML/Gen AI use case development, deployment, and/or monitoring. • Hands-on understanding of AI observability concepts, model performance tracking, and monitoring tools. • Experience in documenting technical workflows, onboarding guides, and reporting dashboards. • Proficiency in working with AI platforms, cloud tools (e.g., Azure, GCP, AWS), and basic scripting. Required Skills: • Use Case Onboarding Support: Partner with AI/Gen AI use case teams across functions to guide them through the onboarding process onto the AI observability platform. • Troubleshooting & Enablement: Assist teams in identifying and resolving onboarding issues and recommend best practices for observability integration. • Stakeholder Engagement: • Conduct regular check-ins with use case owners to gather feedback, resolve issues, and provide updates on onboarding progress. • Documentation & Reporting: • Maintain up-to-date onboarding trackers, create documentation and status reports for leadership, and develop onboarding artifacts. • Cross-Functional Coordination: Act as a liaison between use case teams and the AI observability product team to share progress, blockers, and improvement opportunities. • Monitoring Support: • Provide assistance with bug fixes and other platform support activities that ensure ongoing monitoring and value realization. • Use Case Health Reporting: • Generate periodic reports on use case performance, health metrics, and provide insights or recommendations to enhance outcomes. • Knowledge Contribution: • Help build knowledge base and reusable onboarding documentation, FAQs, templates, and best practices.

About the Role We are looking for a Senior Data Scientist to come and work on our growing AI stack. You will be working with a team of highly skilled and motivated data scientists and machine learning engineers. If you are excited about natural language understanding and machine translation, AppZen is the right place for you to apply and grow your skills. Key Responsibilities: Solid understanding of machine learning fundamentals, and familiar with standard algorithms and techniques Solid understanding of Python programming, including core data structures (lists, dicts, sets, tuples), object-oriented design, and writing clean, modular, and maintainable code. Experience with code optimization techniques, including efficient memory and runtime usage, vectorization (NumPy/Pandas), and debugging performance bottlenecks. Hands-on experience with LLMs such as GPT, LLaMA, or Claude, including evaluation and integration into production pipelines. Proficiency in using GenAI frameworks and tools (e.g., Hugging Face Transformers, LangChain, OpenAI APIs, vLLM, or AutoGen) to build, customize, and deploy language-based solutions. Ability to analyze, evaluate, and optimize LLM outputs for accuracy, safety, relevance, and bias mitigation in enterprise use cases. Work with internal and external stakeholders on program management Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful Excellent written and verbal technical communication skills; communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions M.Tech/B.Tech. or equivalent experience in Computer Science, Engineering, Statistics, or other relevant technical field Must have 6+ years of industry experience You are a team player Nice-to-Have: Track record of having developed novel algorithms, e.g. publications in one or more of the following: KDD, WWW, NIPS, ISWC, NAACL, ACL, SIGIR, EMNLP, ICML etc Good Understanding of MLOps tools/processes like ElasticSearch, Jenkins, Docker is plus. Expertise in building and fine-tuning LLM models using Transformers and RAG systems.

Extensive knowledge in machine learning concepts, models and algorithms Good knowledge on Machine Learning Operations or Development Operations Good knowledge on software engineering DevOps Well versed in major machine learning operations platforms and providers Quickly adapt to new platforms and tools Can you say Yes, I will! to the following Deliver end-to-end AA & AI model deployment by actively conducting the technical operationalization steps Support the use case squads in code QA/QC to be ready for deployment Contribute to cross-functional problem-solving sessions with use case squad and provide inputs regarding productization Orchestrate production pipeline and model/code transfer to production environment. Ensure it is working as intended Ensure the code transferred to production is bug-free, all sources are setup for production servers Find run-time performance improvement and decide which ML technologies will be used in production environment Monitor model performance, model drift and data drift and take appropriate remedial action to correct model performance Collaborate with other stakeholders (BT, EDM, BU) to ensure all infrastructure requirements are completed for model productization Document the various approach, techniques used in operationalization for maintainability and knowledge sharing purpose Great understanding of different MLOps concepts and platforms Mentor and coach MLOps Engineer on MLOps techniques, processes, new platforms, ways of working and supporting in their use case operationalization delivery

About the Role: We are seeking a highly experienced and visionary AI Senior Technical Lead to drive the technical direction and execution of our AI initiatives. This role is pivotal in shaping our AI strategy, leading a team of talented AI engineers, and ensuring the delivery of innovative and impactful AI solutions. As a technical leader, you will be responsible for defining architectural vision, driving best practices, and fostering a culture of technical excellence across diverse AI domains. Responsibilities: Technical Leadership & Strategy: Define and communicate the technical vision and strategy for AI projects. Lead the architectural design and implementation of complex AI systems. Evaluate and recommend emerging AI technologies and methodologies. Drive the adoption of best practices for AI development, deployment, and maintenance. Contribute to the strategic planning of AI initiatives, aligning them with business goals. Team Leadership & Mentorship: Lead and mentor a team of AI engineers, providing technical guidance and support. Foster a collaborative and innovative team environment. Conduct code reviews and ensure code quality. Identify and address skill gaps within the team. Facilitate knowledge sharing and continuous learning. AI System Development & Implementation: Oversee the development and deployment of scalable and robust AI solutions. Ensure the performance, reliability, and security of AI systems. Drive the development of AI pipelines and infrastructure. Lead the integration of AI models with existing systems and applications. Troubleshoot and resolve complex technical issues. Research & Innovation: Stay abreast of the latest advancements in AI and machine learning. Identify opportunities to apply AI to solve complex business challenges, including opportunities within Generative AI. Drive research and development efforts to explore new AI technologies. Evaluate and prototype new AI solutions. Collaboration & Communication: Collaborate with cross-functional teams, including product managers, data scientists, and software engineers. Communicate complex technical concepts to both technical and non-technical audiences. Provide technical presentations and demonstrations. Document technical designs, code, and processes. Required Skills and Qualifications: Education: Batchelors or Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 8+ years of experience in AI/ML development, with a proven track record of leading complex AI projects. Extensive experience in designing and implementing scalable AI systems. Proven experience in leading and mentoring technical teams. Deep understanding of machine learning and deep learning algorithms and architectures. Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Technical Skills: Expertise in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of AI infrastructure and deployment strategies. Experience with MLOps best practices. Experience with vector databases, and LLM implementations. Proficiency in software development principles and best practices. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes). Soft Skills: Exceptional leadership and communication skills. Strong problem-solving and analytical skills. Ability to think strategically and drive innovation. Excellent interpersonal and collaboration skills. Strong presentation skills. Preferred Qualifications: Experience with Generative AI technologies and methodologies (e.g., GANs, Diffusion Models, Transformers for generation). Experience with natural language processing (NLP) or computer vision. Contributions to open-source AI projects. Experience with distributed systems and big data technologies. Experience with prompt engineering.

Overview: We are seeking an exceptional and technically accomplished Senior Data Scientist to join our rapidly growing team. This role is ideal for a hands-on AI expert with deep experience in Large Language Models (LLMs) , Natural Language Processing (NLP) , Cognitive AI , Conversational AI , and Agentic AI systems . You will work on designing, developing, and scaling state-of-the-art AI solutions that drive business innovation, operational intelligence, and customer experience transformation. This is a high-impact individual contributor role, focused on technical excellence and product-grade AI development. Key Responsibilities LLM & Cognitive AI Solution Development Architect and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral) using transfer learning, PEFT, and retrieval-augmented generation (RAG). Develop Agentic AI architectures with autonomous behavior and multi-agent collaboration capabilities. Apply prompt engineering , in-context learning , and tool former-style techniques to enable complex reasoning and task execution. Build Conversational AI systems using Transformer-based backbones and orchestration tools (LangChain, Haystack, Rasa, Semantic Kernel). Natural Language Processing (NLP) Design and implement advanced NLP pipelines for semantic search, summarization, NER, text classification, and knowledge extraction. Utilize and integrate tools such as SpaCy , BERT , RoBERTa , GloVe , Word2Vec , NLTK , and TextBlob . Conduct advanced text preprocessing, dependency parsing, sentiment analysis, tokenization, and multilingual NLP modeling. AI/ML Engineering Build scalable ML pipelines with FastAPI, gRPC, and RESTful interfaces. Containerize services using Docker and deploy to production environments via Kubernetes and cloud-native workflows. Integrate models into real-time and batch data systems, optimizing for latency, throughput, and reliability. Cloud & Infrastructure Develop and deploy solutions on AWS , Azure , or Google Cloud Platform (GCP) . Leverage services like SageMaker, Vertex AI, Azure ML Studio, and serverless orchestration tools. MLOps & CI/CD Design and maintain end-to-end MLOps pipelines using tools like MLflow, Kubeflow, or TFX for reproducibility and traceability. Automate model testing, monitoring, versioning, and rollback strategies in production. Big Data & Analytics Apply Spark, Hadoop, and Hive to process large-scale datasets efficiently. Perform complex data transformations and statistical modeling to extract actionable insights. Database & Data Engineering Interface with SQL and NoSQL systems (PostgreSQL, MongoDB, DynamoDB, etc.) for efficient data retrieval and processing. Design data schemas and optimize query performance for AI-centric applications. Cross-functional Collaboration Work closely with product managers, engineers, and domain experts to identify high-impact problems and deliver AI-driven solutions. Communicate findings and solution architectures clearly to technical and non-technical stakeholders. Technical Skills Expert in Python , PyTorch, HuggingFace Transformers, LangChain, and OpenAI/Anthropic/LLama APIs. Deep understanding of Transformer architectures , Attention Mechanisms , and LLM fine-tuning techniques . Familiarity with Agentic AI paradigms , including memory management, autonomous goal completion, and tool use. Strong experience with cloud platforms, container orchestration (Docker + Kubernetes), and deployment automation. Proficient in statistical modeling, probabilistic reasoning, and experimental design. Bonus Experience in Online Reputation Management (ORM) or product-centric platforms . Publications or open-source contributions in AI/ML/NLP.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).

Job Requirements Education: Bachelors degree (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Masters degree preferred (MBA/MS/M.Tech in Computer Science or related field) Experience: 5–7 years in a Data Science/Advanced Analytics role Behavioral Skills: Delivery Excellence Business Orientation Social Intelligence Innovation and Agility Knowledge & Technical Skills: Functional analytics experience (Supply Chain, Marketing, Customer Analytics, etc.) Statistical modeling using tools such as R, Python, KNIME Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Experience building and evaluating machine learning models MLOps tools and practices (MLflow, DVC, Docker, etc.) Strong Python programming (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Experience with big data technologies (AWS, Azure, GCP, Hadoop, Spark) Familiarity with relational (MySQL, SQL Server) and non-relational (MongoDB, DynamoDB) databases BI and reporting tools (Power BI, Tableau, Alteryx) Proficiency with Microsoft Office applications (especially Excel) Roles & Responsibilities Analytics & Strategy: Analyze large-scale structured and unstructured data to develop insights and machine learning models across various business domains Apply statistical and machine learning techniques to generate value from operational, financial, and customer data Recommend best-fit algorithms and models with clear justifications for business use Leverage cloud platforms for modeling and big data analysis; utilize data visualization tools to communicate results Operational Excellence: Follow industry-standard coding practices and development lifecycles Formulate hypotheses, develop analytics frameworks, and bring structure to complex problems Collaborate with Data Engineering to maintain core data infrastructure and automate analytical processes Stakeholder Engagement: Work cross-functionally with business stakeholders, engineers, and visualization experts to deliver impactful projects Communicate complex models and results to non-technical stakeholders in a clear and compelling way

Role & responsibilities Python + MLOPS Preferred candidate profile immediate to 15 days

Job Title: Technical Architect Generative AI Experience: 1418 Years Location: Noida Employment Type: Full-Time Job Summary: We are looking for a hands-on Technical Architect Generative AI to lead the design and implementation of AI-driven solutions across cloud-native environments. This role requires deep expertise in GenAI models, LLMs, Python, .NET Core, and Azure. The ideal candidate will actively contribute to coding, solution architecture, PoCs, and guide teams in applying GenAI to real-world business scenarios. Key Responsibilities: AI & Application Development Design and implement GenAI use cases (e.g., document summarization, conversational agents, RAG pipelines). Build and integrate LLMs using Python and Azure AI services. Develop scalable backend services with .NET Core Web APIs . Create modern frontends using Angular (13+) or React . Build PoCs and AI accelerators for enterprise-grade use cases. Architecture & System Design Architect and lead implementation of GenAI/LLM-based solutions on Azure . Build event-driven systems using Kafka, Azure Event Grid , or similar. Drive adoption of cloud-native patterns , security guidelines, and DevOps practices. Enforce code quality (SonarQube), security (Guiderails), and CI/CD pipelines. Stakeholder Collaboration Partner with product owners and business teams to translate workflows into GenAI-driven applications. Collaborate with other architects to define the AI/ML roadmap. Present architectural solutions and ROI-focused GenAI use cases to stakeholders. Leadership & Mentoring Conduct code reviews, performance tuning, and technical troubleshooting. Mentor developers on Python, .NET, LLM integration, and AI solution patterns. Contribute to knowledge sharing and technical upskilling across teams. Must-Have Skills: Programming & Frameworks Python : LLM integration, agentic frameworks, prompt engineering .NET Core : Web API, Entity Framework Angular 13+ / React , TypeScript Cloud & DevOps Azure AI Services : Cognitive Services, AI Builder, OpenAI/Foundry, Logic Apps Azure DevOps : CI/CD, Infrastructure-as-Code (ARM/Bicep) Event-driven architectures using Kafka/Event Grid AI/ML Expertise Generative AI, LLM fine-tuning, prompt design, RAG pipelines MLOps and integration of models in production environments Familiarity with tools like GitHub Copilot Qualifications: 1418 years of overall experience in software architecture and development At least 5+ years in AI/ML and cloud-native solutioning Bachelor's or Master's degree in Computer Science, Engineering, or related field Preferred: Azure Solutions Architect Expert or similar certifications Proven experience in enterprise-scale AI implementations (GitHub/GitLab links are a plus) Soft Skills: Strong communicator with ability to present technical ideas to stakeholders Team leadership and Agile methodology experience Innovation mindset and problem-solving orientation Reach Out: 9045052073

We are seeking an experienced AI Lead with a minimum of 10 years of industry experience in the field of Artificial Intelligence. The ideal candidate will have a proven track record of successfully leading and delivering multiple projects in Machine Learning, Deep Learning, and Natural Language Processing (NLP). Additionally, they should possess sound knowledge in Generative AI and Large Language Models (LLMs). Responsibilities: Project Leadership: Lead end-to-end AI projects, from conception to delivery, ensuring alignment with business objectives and stakeholder requirements. Technical Expertise: Serve as a subject matter expert in AI, providing guidance and support to the team in the development and implementation of advanced machine learning and deep learning models. Research and Development: Stay abreast of the latest advancements in AI technologies and methodologies, conducting research and experiments to drive innovation and enhance project outcomes. Team Management: Manage and mentor a team of junior data scientists and machine learning engineers, providing technical guidance, coaching, and professional development opportunities. Collaboration: Collaborate closely with cross-functional teams, including product management, engineering, and business development, to identify opportunities for leveraging AI to solve business challenges and drive growth. Quality Assurance: Ensure the quality and accuracy of AI solutions through rigorous testing, validation, and performance monitoring. Strategic Planning: Contribute to the development of AI strategies and roadmaps, outlining key initiatives and milestones to support business objectives. Qualifications: Bachelors degree in computer science, Engineering, Mathematics, or related field. Advanced degree (Master's or Ph.D.) preferred. Minimum of 10 years of industry experience in artificial intelligence, with a focus on machine learning, deep learning, and NLP. Proven track record of leading and delivering multiple AI projects from conception to completion. Expertise in machine learning frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn. Expertise in MLOps tools, Databricks, and AI services offered by cloud platforms such as Azure, AWS, and GCP. Experience with Generative AI and Large Language Models (LLMs) such as GPT, BERT, or Transformer models. Excellent leadership and communication skills, with the ability to effectively manage and mentor a team of junior data scientists and ML engineers. Strong analytical and problem-solving skills, with a keen attention to detail and a commitment to delivering high-quality results. Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities and requirements. Location - Noida,Mumbai,Hyderabad,Kochi.

The ideal candidate will design, develop, and implement AI-driven solutions that enhance our products and business operations. This role requires a deep understanding of machine learning algorithms, data processing, and deployment practices.