31 Ml Flow Jobs - Page 2

Job role & responsibilities:- Collaborate with different teams to propose AI solutions on different use cases across the insurance value chain, with a focus on AIops and MLOps Research, build, and deploy AI models as part of the broader AI team, leveraging AIops and MLOps practices for efficient model management Contribute to our DevOps practices using OpenShift or Azure ML DevOps Technical Skills, Experience & Qualification required:- Expertise is required in the following fields: 6-9 years of progressive experience in AI and ML, with a focus on AIops and MLOps Experience in ML Flow or Cube Flow or Airflow, ML Ops, more in to production deployment Experience in deploying and managing AI models in production environments using Azure ML DevOps or OpenShift Implementation of at least 5 AI projects, preferably with experience in AIops and MLOps Experience with Azure, OpenShift, MLFlow DevOps for model deployment, monitoring, and management Setting up CI/CD pipelines using Azure DevOps, Jenkins, etc. Hands-on experience with Generative AI tech LLMs, RAG, Prompt Engineering Broad understanding of machine learning algorithms and techniques, including LLMs/SLMs, CNNs) RNNs, transformers, and attention mechanisms Immediate Joiners will be preferred

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

Must have skills: ML algorithms, NLP and Predictive Analytics, Conversational Analytics, Python, Cloud Knowledge (Azure/AWS/GCP), Proficiency in BI tools (Power BI/Tableau/ Qlik Sense/ThoughtSpot/Figma etc.). Leverages artificial intelligence and machine learning techniques to enhance BI processes along with consulting experience of AI driven BI Transformations (Defining BI Governance, Operating model, Assessment Framework etc.) Good to have skills: Knowledge of Gen AI Models implementation (Open AI, Mistral, Phi-2, Solar, Claude 3 etc.), Agentic architecture implementation WHATS IN IT FOR YOU Youll be part of a diverse, vibrant, BI Strategy team which has dynamic and innovative group of creating Data and BI Strategy & Consulting professionals. We understand the vision and mission of our customers & help them by developing innovative BI Strategy with value driven use cases, roadmap & technological solutions that drive business growth and innovation. As a key pillar of our organization, the Engineering Products team worked on various fields from BI , Data & AI perspective- BI Strategy, AI Enabled BI Strategy, Data Modelling, Data Architecture, Industry & AI Value strategy etc. that helps our customers in setting up strong data platform foundation & target roadmap to scaling & evolve towards achieving AI/GEN AI & advanced analytics vision to meet the evolving future needs of technology advancement. What you would do in this role Participate in visioning workshop & develop innovative BI Strategy & architecture frameworks tailored to the unique goals and aspirations of our clients, ensuring alignment with their evolving needs and preferences. Conduct comprehensive evaluations of clients' existing processes, technologies, and data ecosystems, uncovering opportunities for AI integration that resonate with Gen AI values and lifestyles. Align with industry & function teams, understand business problems, and translate it to BI , BI Governance , AI enabled BI and Operating Model , Develop target strategy with respect to Business Intelligence, Tools & Technology, BI Operating Model, BI Governance, AI Enabled BI needs along with Key initiatives & roadmap. Propose best suited LLMs (Large Language Model-GPT 3.5, 4, Llama etc.) as per the selection criteria framework & serve as a trusted advisor to our clients, offering expert guidance on AI Enabled BI Propose adoption strategies that resonate with BI and plan persona-based BI strategy for enterprise function. Work closely with cross-functional teams to co-create and implement innovative . He should be able to define personas and persona journey from functional and technical aspects with respect to Business Intelligence Able to architect , delivery and design BI Enabled AI solutions that address the complex challenges faced by customers and businesses. Participate in client engagements with confidence and finesse, overseeing project scope, timelines, and deliverables to ensure seamless execution and maximum impact. Facilitate engaging workshops and training sessions to empower BI Client stakeholders with the knowledge and skills needed to embrace Data driven transformation enabled through AI. Stay abreast of emerging BI , Data and AI analytics trends and technologies, continuously improving internal capabilities and offerings. Participate in BI, AI Enabled BI and Analytics aligned solutions and client demos. Who are we looking for Years of Experience: Candidates should typically have at least 6-9 years of experience in BI strategy, management, or a related field. This experience should include hands-on involvement in developing and implementing BI strategies for clients across various industries. Education: A bachelors or masters degree in computer science, Data Science, Engineering, Statistics, or a related field. Add eligibility: Strong analytical and strategic thinking skills are essential for this role. Candidates should be able to assess clients' business processes, technologies, BI, AI and data infrastructure to find opportunities for BI and AI Enabled BI integration and develop tailored BI strategy frameworks aligned with clients' goals. Displayed expertise in artificial intelligence technologies, including machine learning, natural language processing, computer vision, and deep learning. Candidates should have a solid understanding of AI concepts, algorithms, and their applications in solving real-world business problems. Excellent communication and presentation skills are crucial for effectively articulating complex technical concepts to non-technical stakeholders. Candidates should be able to convey AI strategy recommendations in a clear, concise, and compelling manner. Knowledge of cloud computing services (AWS, Azure, GCP) related to scaled AI and data analytics solutions. The ability to collaborate effectively with cross-functional teams is essential for this role. Candidates should be comfortable working with diverse teams to design and execute AI solutions that address clients' business challenges and deliver measurable results. Candidates should have a strong understanding of Gen AI preferences, behaviors, and values. Candidate should have understanding & working knowledge of various large language models to propose and implement best suited LLMs to our customer based on AI strategies that resonate with Gen AI Working experience with machine learning algorithms and statistical modeling techniques. Knowledge on MLOPs tools and services from strategic mindset will be a plus. Desired experience. Minimum 6 years of experience working with clients in the products industry (Lifesciences, CPG, Industry & Ret that are heavily influenced by AI & Gen AI preferences and behaviors, is highly valued. Candidates who have a deep understanding of AI & Gen AI trends and market dynamics can provide valuable insights and strategic guidance to clients. Minimum 5 years proven experience & deep expertise in developing and implementing AI strategy frameworks tailored to the specific needs and aims of clients within LS, Industry, CPG, and Retail sectors. The ability to craft innovative AI solutions that address industry-specific challenges and drive tangible business outcomes will set you apart. Minimum 6 years strong consulting background with a demonstrated ability to lead client engagements from start to completion. Consulting experience should encompass stakeholder management and effective communication to ensure successful project delivery. Minimum 4 years strong working experience AI implementation lifecycle & working knowledge in the AI and Analytics lifecycle, including problem definition, data preparation, model building, validation, deployment, and monitoring. Tools & Techniques Knowledge of UI/UX design using React, Angular & Visualization tools-Power BI/Tableau/Qlik Sense Knowledge on Cloud and native services around AI & GEN AI implementation-AWS/Azure/ GCP Have worked hands on Programming languages such as Python, R, SQL or Scala. Working knowledge AI and analytics platforms and tools, such as TensorFlow, PyTorch, KNIME, or similar technologies Working Knowledge on NLP (Natural Language Processing) techniques-text summarizer, text classification, Named Entity Recognition etc. Working Knowledge on various machine learning models-Supervised unsupervised, classification, regression model, Reinforcement learning, Neural networks etc., Knowledge on LLMs-Open AIGPT, Llama Index etc. Knowledge of ML Ops deployment, process tools & strategy (ML Flow, AWS Sage maker etc. law. Qualification Experience: Minimum 4 year(s) of experience is required Educational Qualification: B.Tech/BE

We are looking for Indias top 1% Computer Vision Engineers for a unique job opportunity to work with the industry leaders Who can be a part of the community? We are looking for top-tier Computer Vision (CV) Engineers with expertise in image/video processing, object detection, and generative AI If you have experience in this field then this is your chance to collaborate with industry leaders Whats in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 12 months, or freelancing Be a part of an Elite Community of professionals who can solve complex AI challenges Work location could be: Remote (Highly likely) Onsite on client location Deccan AIs Office: Hyderabad or Bangalore Responsibilities: Develop and optimize computer vision models for tasks like object detection, image segmentation, and multi-object tracking Lead research on novel techniques using deep learning frameworks (TensorFlow, PyTorch, JAX) Build efficient computer vision pipelines and optimize models for real-time performance Deploy models using microservices (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure) Lead MLOps practices, including CI/CD pipelines, model versioning, and training optimizations Required Skills: Expert in Python, OpenCV, NumPy, and deep learning architectures (eg, ViTs, YOLO, Mask R-CNN) Strong knowledge in computer vision fundamentals, including feature extraction and multi-view geometry with experience in deploying and optimizing models with TensorRT, Open VINO, and cloud/edge solutions Proficient with MLOps tools (ML flow, DVC), CI/CD, and distributed training frameworks Experience in 3D vision, AR/VR, or LiDAR processing is a plus Nice to Have: Experience with multi-camera vision systems, LiDAR, sensor fusion, and reinforcement learning for vision tasks Exposure to generative AI models (eg, Stable Diffusion, GANs) and large-scale image processing (Apache Spark, Dask) Research publications or patents in computer vision and deep learning Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Hi, We are hiring for ML Developer. Please find the attached JD. Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary Preferred candidate profile Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5 to 5 years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like ML flow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills.

Role Title: AI Platform Engineer Location: Bangalore (In Person in office when required) Key Responsibilities Platform Development and Evangelism: Build scalable AI platforms that are customer-facing. Evangelize the platform with customers and internal stakeholders. • Ensure platform scalability, reliability, and performance to meet business needs. Machine Learning Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining. Implement A/B testing of models. Design APIs for model inferencing at scale. Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. LLM Serving and GPU Architecture: Serve as an SME in LLM serving paradigms. Possess deep knowledge of GPU architectures. Expertise in distributed training and serving of large language models. • Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. Model Fine-Tuning and Optimization: Demonstrate proven expertise in model fine-tuning and optimization techniques. Achieve better latencies and accuracies in model results. Reduce training and resource requirements for fine-tuning LLM and LVM models. LLM Models and Use Cases: Have extensive knowledge of different LLM models. Provide insights on the applicability of each model based on use cases. • Proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. DevOps and LLMOps Proficiency: Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. • Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Skill Matrix LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery. Cloud Knowledge: AWS/Azure/GCP Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert Proficient in Python, SQL, Javascript