16 Ml Flow Jobs

You will be working as an AI Platform Engineer in Bangalore as part of the GenAI COE Team. Your key responsibilities will involve developing and promoting scalable AI platforms for customer-facing applications. It will be essential to evangelize the platform with customers and internal stakeholders, ensuring scalability, reliability, and performance to meet business needs. Your role will also entail designing machine learning pipelines for experiment management, model management, feature management, and model retraining. Implementing A/B testing of models and designing APIs for model inferencing at scale will be crucial. You should have proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. As an AI Platform Engineer, you will serve as a subject matter expert in LLM serving paradigms, with in-depth knowledge of GPU architectures. Expertise in distributed training and serving of large language models, along with proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM, will be required. Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results will be part of your responsibilities. Reducing training and resource requirements for fine-tuning LLM and LVM models will also be essential. Having extensive knowledge of different LLM models and providing insights on their applicability based on use cases is crucial. You should have proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases. Your proficiency in DevOps and LLMOps practices, along with knowledge of Kubernetes, Docker, and container orchestration, will be necessary. A deep understanding of LLM orchestration frameworks such as Flowise, Langflow, and Langgraph is also required. In terms of skills, you should be familiar with LLM models like Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, and Llama, as well as LLM Ops tools like ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, and Azure AI. Additionally, knowledge of databases/data warehouse systems like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, and Google BigQuery, as well as cloud platforms such as AWS, Azure, and GCP, is essential. Proficiency in DevOps tools like Kubernetes, Docker, FluentD, Kibana, Grafana, and Prometheus, along with cloud certifications like AWS Professional Solution Architect and Azure Solutions Architect Expert, will be beneficial. Strong programming skills in Python, SQL, and Javascript are required for this full-time role, with an in-person work location.,

The ML Solutions team within Markets OPS Technology is dedicated to developing solutions using Artificial Intelligence, Machine Learning, and Generative AI. This team is a leader in creating new ideas, innovative technology solutions, and ground-breaking solutions for Markets Operations and Other Line of Businesses. We work closely with our clients and business partners to progress solutions from ideation to production by leveraging the entrepreneurial spirit and technological excellence. The ML Solutions team is seeking a Data Scientist/Machine Learning Engineer to drive the design, development, and deployment of innovative AI/ML and GenAI-based solutions. In this hands-on role, you will leverage your expertise to create a variety of AI models, guiding a team from initial concept to successful production. A key aspect involves mentoring team members and fostering their growth. You will collaborate closely with business partners and stakeholders, championing the adoption of these advanced technologies to enhance client experiences, deliver tangible value to our customers, and ensure adherence to regulatory requirements through cutting-edge technical solutions. This position offers a unique opportunity to shape the future of our AI initiatives and make a significant impact on the organization. Key Responsibilities: - Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks. - Mentoring Young Talents: Mentoring team, guiding data analysts/ML engineers from concept to production. This involves fostering technical growth, providing project oversight, and ensuring adherence to best practices, ultimately building a high-performing and innovative team. - Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation. - Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field. - Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services. Skills & Qualifications: - 8 to 13 years of Strong hands-on experience in Machine Learning, delivering complex solutions to production. - Experience with Generative AI technologies essential. - Understanding of concepts like supervised, unsupervised, clustering, embedding. - Knowledge of NLP, Name Entity Recognition, Computer Vision, Transformers, Large Language Models. - In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar. - Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy, OpenCV. - Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch, Keras. - Proficiency in Python Software Development, following Object-Oriented design patterns and best practices. - Strong background in mathematics: linear algebra, probability, statistics, and optimization. - Experience with evaluation, scoring with a framework like ML Flow - Experience of Docker container and edited a Docker file, experience with K8s is a plus. - Experience with Postgres and Vector DBs a plus. - Excellent problem-solving skills and the ability to think creatively. - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - Publications and contributions to the AI research community are a plus. - Masters degree/Ph. D. or equivalent experience in Computer Science, Data Science, Statistics, or a related field. - 8-12 years of experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.,

Min 1-3 yrs of exp in data science,NLP&Python Exp in PyTorch,Scikit-learn,and NLP libraries(NLTK,SpaCy,Hugging Face) Help deploy AI/ML solutions on AWS,GCP/Azure Exp in SQL for data manipulation & analysis Exp in Big Data processing Spark,Pandas,Dask

You will be a key member of the Data + AI Pipeline team, leading to the integration of Kubeflow, Kubernetes, Docker, Keda, and Python technologies. Your role will involve developing and maintaining AI pipelines that support various projects, ensuring seamless and efficient data processing, model training, and deployment. As part of a dynamic and interdisciplinary team, you will collaborate with experts in data engineering, AI, and software development to create robust and scalable solutions. Job Description • We are seeking a motivated and experienced Data + AI Pipeline Engineer to lead the development and maintenance of our KION Machine Vision AI pipeline infrastructure. • As a Data + AI Pipeline Lead, you will provide technical leadership and strategic direction to the team, be responsible for designing and implementing scalable and efficient AI pipelines using Kubeflow, Kubernetes, Docker, Keda, and Python. • You will collaborate with cross-functional teams to understand project requirements, define data processing workflows, and ensure the successful deployment of machine learning models. • Your role will involve integrating and optimizing data processing and machine learning components within our pipeline architecture. • You will provide technical leadership and mentorship to junior team members, guiding them in the design and implementation of AI pipelines and fostering their professional growth. • Conduct code reviews and provide constructive feedback to ensure the quality, readability, and maintainability of codebase across the team. • Collaborate with the software engineering team to ensure the seamless integration of AI pipelines with other software applications. • Implement and maintain CI/CD pipelines to automate the deployment of AI models and ensure continuous integration and delivery. • Work closely with external partners and vendors to leverage the latest advancements in AI and data processing technologies. Qualifications : • A university degree with a technical focus, preferably in computer science, data science, or a related field. • 10+ years of experience in building and maintaining large-scale AI pipeline projects, with at least 2 years in a leadership or managerial role. • Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and services for data processing, storage, and deployment. • Strong programming skills in Python and proficiency in using libraries and frameworks for data manipulation, analysis, and visualization (e.g., pandas, NumPy, matplotlib). • Knowledge of containerization technologies (e.g., Docker, Kubernetes) and orchestration tools for deploying and managing machine learning pipelines at scale. • Expertise in designing and optimizing data processing workflows and machine learning pipelines. • Strong communication skills to collaborate effectively with cross-functional teams and present complex technical concepts in a clear manner. • Experience with CI/CD, automation, and a strong understanding of software engineering best practices. • Ability to overview complex software architectures and contribute to future-oriented developments in the field of AI and data processing. • Excellent problem-solving skills and the ability to work in a dynamic and fast-paced environment. • Leading and guiding, technical mentoring to the team • Very good English skills, both written and verbal, to facilitate effective communication within the global team.

Skills required for ML engineering expert : : 5+ years of experience in Python programing and performance tuning and optimization. Experience on ML engineering, Knowledge on Feast, Kubeflow and MLFlow. Deep understanding on NumPy , Pandas, data frames etc. Working knowledge on bigdata environment and data science model added advantage. Strong analytical and problem-solving skills, with attention to detail and ability to work in a fast-paced environment Excellent communication and collaboration skills, with ability to work with cross-functional teams Knowledge of machine learning and data science concepts

Role & responsibilities: Looking for 5 to 8 years experience of ML Engineer with strong Azure Cloud DevOps with even stronger DABs DevOps skills with even stronger DABs Databricks Asset Bundles implementation knowledge. 1 Azure Cloud Engineer 2 Azure DevOps CICD experienced in DABs 3 ML Engineer for deployment Translate business requirement into technical solution Implementation of MLOPS Scalable solution using AIML and reduce the risk of Fraud and other fiscal crisis Creating MLOPS Architecture and implementing it for multiple models in a scalable and automated way Designing and implementing end to end ML solutions Operationalize and monitor machine learning models using high end tools and technologies Design implementation of DevOps principles in Machine Learning Data Science quality assurance and testing Collaborate with data scientists engineers and other key stakeholders Preferred candidate profile: Azure Cloud Engineering Design implement and manage scalable cloud infrastructure on Microsoft Azure Ensure high availability performance and security of cloud based applications Collaborate with cross functional teams to define and implement cloud solutions Azure DevOps CICD Develop and maintain CICD pipelines using Azure DevOps Automate deployment processes to ensure efficient and reliable software delivery Monitor and troubleshoot CICD pipelines to ensure smooth operation DABs Databricks Asset Bundles Implementation Lead the implementation and management of Databricks Asset Bundles Optimize data workflows and ensure seamless integration with existing systems Provide expertise in DABs to enhance data processing and analytics capabilities Machine Learning Deployment Deploy machine learning models into production environments Monitor and maintain ML models to ensure optimal performance Collaborate with data scientists and engineers to integrate ML solutions into applications.

As a Senior Software Engineer on the AI Engineering Team at Cotiviti, you will be a leading force in developing robust, scalable machine learning solutions for healthcare applications. This senior-level position involves significant responsibility, including leading design and development efforts, mentoring junior engineers, and ensuring the delivery of high-quality solutions. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, Math, or a related field, or equivalent experience 7+ years of experience with Hadoop tech stack (Spark, Kafka) Should have experience with batch processing on large scale data with Spark and real-time without Spark Proficiency in programming languages such as Scala or Python Extensive experience with Kafka and data streaming platforms Advanced knowledge of Data Bricks on AWS or similar cloud platforms Proven experience building and maintaining microservices Deep understanding of data architecture principles Experience leading design and development of large systems Proficiency with CI/CD tools like Jenkins Experience with Unix/Linux operating systems Familiarity with Agile processes and tools like Jira and Confluence Strong drive to learn and advocate for development best practices Strong knowledge on troubleshooting and optimizing Spark applications Preferred Qualifications: Experience with Data Bricks on Azure/AWS Experience with Kafka, DataStream/DataFrame/DataSet Advanced proficiency with containerization tools like Docker, Kubernetes Knowledge of machine learning frameworks and tools such as DataRobot, H2O, ML Flow Experience with big data tools like Spark, Scala, Oozie, Hive or similar Streaming technologies Kafka, SparkStreams, RabbitMQ Experience with Continuous Integration and Delivery, unit testing, and functional automation testing Having API development experience will be a good addition. Healthcare domain experience will be a plus. Responsibilities: Lead the development and implementation of machine learning solutions for healthcare applications Guide and mentor a team of developers and testers Collaborate with data scientists and other engineers to design and build scalable solutions Write, test, and maintain high-quality code along with Code coverage Lead design and code review sessions Troubleshoot and resolve complex technical issues Document your work and share knowledge with the team Advocate for and implement development best practices Train and mentor junior engineers and software engineers

Role & responsibilities 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 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. Preferred candidate profile

We are seeking a Senior Python DevOps Engineer to develop Python services and build CI/CD pipelines for AI/data platforms. Must have strong cloud, container, and ML workflow deployment experience. Required Candidate profile Experienced Python DevOps engineer with expertise in CI/CD, cloud, and AI platforms. Skilled in Flask/FastAPI, Airflow, MLFlow, and model deployment on Dataiku and OpenShift.

We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders

Exciting opportunity for an ML Platform Specialist to join a leading technology-driven firm. You will be designing, deploying, and maintaining scalable machine learning infrastructure with a strong focus on Databricks, model lifecycle, and MLOps practices. Location: Gurugram (Hybrid) Your Future Employer Our client is a leading digital transformation partner driving innovation across industries. With a strong focus on data-driven solutions and cutting-edge technologies, they are committed to fostering a collaborative and growth-focused environment. Responsibilities Designing and implementing scalable ML infrastructure on Databricks Lakehouse Building CI/CD pipelines and workflows for machine learning lifecycle Managing model monitoring, versioning, and registry using MLflow and Databricks Collaborating with cross-functional teams to optimize machine learning workflows Driving continuous improvement in MLOps and automation strategies Requirements Bachelors or Masters in Computer Science, ML, Data Engineering, or related field 3-5 years of experience in MLOps, with strong expertise in Databricks and Azure ML Proficient in Python, PySpark, MLflow, Delta Lake, and Databricks Feature Store Hands-on experience with cloud platforms (Azure/AWS/GCP), CI/CD, Git Knowledge of Terraform, Kubernetes, Azure DevOps, and distributed computing is a plus Whats in it for you Competitive compensation with performance-driven growth opportunities Work on cutting-edge MLOps infrastructure and enterprise-scale ML solutions Collaborative, diverse, and innovation-driven work culture Continuous learning, upskilling, and career development support

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.