93 Deploying Models Jobs - Page 2

Educational Bachelor of Engineering Service Line Quality Responsibilities Data collection, profiling, EDA & data preparation AI Model development, tuning & validation Visualization tools (e.g., PowerBI, tableau) Present findings to business users & project management teams Propose ML based solution approaches and estimates for new use cases Contribute to AI based modules in Infosys solutions development Explore new advances in AI continuously and execute PoCs Mentoringguide other team members ML algorithms AI domainsNLP, speech, computer vision Supervised, Unsupervised, Reinforcement learning Tools for data analysis, auto ML, model deployment and scaling Knowledge of datasets ProgrammingPython Databases Knowledge of cloud platforms Azure/AWS/GCP. Preferred Skills: Technology-Machine Learning-AI/ML Solution Architecture and Design

Machine Learning Engineer Fraud Detection Job Title : Machine Learning Engineer Fraud Detection Location : Chennai, Hyderabad, Bangalore Experience : 1-4 Role Summary: Design and deploy machine learning models to detect and prevent fraudulent activities in real-time across payment and lending platforms. Key Responsibilities: Build and train models for anomaly detection, behavioural analysis, and risk scoring. Work with data scientists and engineers to deploy models in production. Continuously monitor model performance and retrain as needed. Integrate models with fraud detection systems and alert mechanisms. Stay updated on emerging fraud tactics and ML techniques. Qualifications: 36 years in machine learning or data engineering. Strong programming skills in Python, TensorFlow, PyTorch, or similar. Experience with fraud detection systems and real-time data pipelines. Knowledge of supervised and unsupervised learning techniques. Familiarity with financial regulations and data privacy standards.

We are seeking an experienced professional in AI and machine learning with a strong focus on large language models (LLMs) for a 9-month project. The role involves hands-on expertise in developing and deploying agentic systems and working with transformer architectures, fine-tuning, prompt engineering, and task adaptation. Responsibilities include leveraging reinforcement learning or similar methods for goal-oriented autonomous systems, deploying models using MLOps practices, and managing large datasets in production environments. The ideal candidate should excel in Python, ML libraries (Hugging Face Transformers, TensorFlow, PyTorch), data engineering principles, and cloud platforms (AWS, GCP, Azure). Strong analytical and communication skills are essential to solve complex challenges and articulate insights to stakeholders.

Project Role : Application Support Engineer Project Role Description : Act as software detectives, provide a dynamic service identifying and solving issues within multiple components of critical business systems. Must have skills : OpenShift Virtualization Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Support Engineer, you will act as software detectives, providing a dynamic service that identifies and resolves issues within various components of critical business systems. Your typical day will involve collaborating with team members to troubleshoot problems, analyzing system performance, and ensuring the smooth operation of applications that are vital to business functions. You will engage with stakeholders to understand their needs and provide timely solutions, contributing to the overall efficiency and effectiveness of the organization. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Assist in the development and implementation of best practices for application support.- Provide training and guidance to junior team members on troubleshooting techniques. Professional & Technical Skills: - Must To Have Skills: Proficiency in OpenShift Virtualization.- Good To Have Skills: Experience with Kubernetes and container orchestration.- Strong understanding of cloud infrastructure and deployment models.- Familiarity with monitoring tools and performance tuning.- Experience in scripting languages for automation tasks. Additional Information:- The candidate should have minimum 3 years of experience in OpenShift Virtualization.- This position is based at our Gurugram office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Technology Architect Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs. Must have skills : Cloud Infrastructure Good to have skills : Infrastructure Service Management, SAP GRC( AC.PC,RM)Minimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Technology Architect, you will review and integrate all application requirements, including functional, security, integration, performance, quality, and operations requirements. You will also review and integrate the technical architecture requirements and provide input into final decisions regarding hardware, network products, system software, and security. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Lead the design and implementation of cloud infrastructure solutions.- Collaborate with stakeholders to understand and define infrastructure requirements.- Ensure the scalability, security, and reliability of cloud infrastructure systems. Professional & Technical Skills: - Must To Have Skills: Proficiency in Cloud Infrastructure.- Strong understanding of cloud service models and deployment models.- Experience with infrastructure automation tools like Terraform or Ansible.- Knowledge of networking concepts and protocols.- Hands-on experience with cloud security best practices. Additional Information:- The candidate should have a minimum of 15 years of experience in Cloud Infrastructure.- This position is based at our Mumbai office.- A 15 years full-time education is required. Qualification 15 years full time education

We are looking for a Machine Learning Engineer with expertise in MLOps (Machine Learning Operations) or LLMOps (Large Language Model Operations) to design, deploy, and maintain scalable AI/ML systems. You will work on automating ML workflows, optimizing model deployment, and managing large-scale AI applications, including LLMs (Large Language Models) , ensuring they run efficiently in production. Key Responsibilities: Design and implement end-to-end MLOps pipelines for training, validation, deployment, monitoring, and retraining of ML models. Optimize and fine-tune large language models (LLMs) for various applications, ensuring performance and efficiency. Develop CI/CD pipelines for ML models to automate deployment and monitoring in production. Monitor model performance, detect drift , and implement automated retraining mechanisms. Work with cloud platforms ( AWS, GCP, Azure ) and containerization technologies ( Docker, Kubernetes ) for scalable deployments. Implement best practices in data engineering , feature stores, and model versioning. Collaborate with data scientists, engineers, and product teams to integrate ML models into production applications. Ensure compliance with security, privacy, and ethical AI standards in ML deployments. Optimize inference performance and cost of LLMs using quantization, pruning, and distillation techniques . Deploy LLM-based APIs and services, integrating them with real-time and batch processing pipelines. Key Requirements: Technical Skills: Strong programming skills in Python, with experience in ML frameworks ( TensorFlow, PyTorch, Hugging Face, JAX ). Experience with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker, Airflow). Deep understanding of LLM architectures , prompt engineering, and fine-tuning. Hands-on experience with containerization (Docker, Kubernetes) and orchestration tools . Proficiency in cloud services (AWS/GCP/Azure) for ML model training and deployment. Experience with monitoring ML models (Prometheus, Grafana, Evidently AI). Knowledge of feature stores (Feast, Tecton) and data pipelines (Kafka, Apache Beam). Strong background in distributed computing (Spark, Ray, Dask) . Soft Skills: Strong problem-solving and debugging skills. Ability to work in cross-functional teams and communicate complex ML concepts to stakeholders. Passion for staying updated with the latest ML and LLM research & technologies . Preferred Qualifications: Experience with LLM fine-tuning , Reinforcement Learning with Human Feedback ( RLHF ), or LoRA/PEFT techniques . Knowledge of vector databases (FAISS, Pinecone, Weaviate) for retrieval-augmented generation ( RAG ). Familiarity with LangChain, LlamaIndex , and other LLMOps-specific frameworks. Experience deploying LLMs in production (ChatGPT, LLaMA, Falcon, Mistral, Claude, etc.) .

Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity? Must have skills required: Voice AI, Voice AI products, AI models, Large Language Models (LLMs), Python, Model deployment, Building AI Models, ASR models, Text-to-Speech (TTS) I-Stem is Looking for: You will: Develop, test, and refine end-to-end voice agent models (ASR, NLU, dialog management, TTS) Stress-test agents in noisy, real-world scenarios and iterate for improved robustness and low latency Research and prototype cutting-edge techniques (e.g. robust speech recognition, adaptive language understanding) Partner with backend and frontend engineers to seamlessly integrate AI components into live voice products Monitor agent performance in production, analyze failure cases, and drive continuous improvement You are: An AI/Software Engineer with hands-on experience in speech-centric ML (ASR, NLU or TTS) Skilled in building and tuning transformer-based speech models and handling real-time audio pipelines Obsessed with reliability: you design experiments to push agents to their limits and root-cause every error A clear thinker who deconstructs complex voice interactions from first principles Passionate about making voice technology inclusive and accessible for diverse users Comfortable moving fast in a small team, yet dogged about code quality, testing and reproducibility

Your Role Must have experience with Machine Learning Model Development Expert Level Proficiency in Data Handling (SQL) Hands-on with Model Engineering and Improvement Strong experience in Model Deployment and Productionlization Your Profile Extensive experience in developing and implementing machine learning, Deep Learning, NLP models across various domains, Strong proficiency in Python, including relevant libraries and frameworks for machine learning, such as scikit-learn, XGBoost and Keras. Ability to write efficient, clean, and scalable code for model development and evaluation. Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Ability to analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance. Strong expertise in deploying machine learning models to production systems. Familiarity with the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments. What you will love about working here We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance Our focus will be your career growth & professional development to support you in exploring the world of opportunities. Equip yourself with valuable certifications & training programmes in the latest technologies such as AIML, Machine Learning The role is applicable for women candidates only. D&I Disclaimer: We are committed to fostering a diverse and inclusive workplace that values and celebrates differences. We believe that diversity in all its forms enriches our organization, promotes innovation, and drives success. We are dedicated to providing equal opportunities for all individuals, regardless of discrimination of any kind, including but not limited to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, neurodiversity, or veteran status. Our commitment extends to embracing all forms of diversity. We actively encourage candidates from diverse backgrounds to apply and join us in shaping a more inclusive future together

We are looking for top-tier Machine Learning Engineers with proven expertise in building, deploying, and optimizing AI models. If you're passionate about AI innovation and ready to collaborate with leading experts, this is your opportunity to join an elite professional community and solve complex real-world challenges. Responsibilities Design, optimize, and deploy machine learning models for production environments Implement scalable feature engineering workflows and data pipelines Use deep learning frameworks such as TensorFlow and PyTorch Manage models in production with Docker, Kubernetes, and similar tools Automate ML workflows and ensure robust versioning, logging, and real-time monitoring Comply with model governance, security, and regulatory best practices Work with large-scale datasets and develop reusable feature stores Build and maintain CI/CD pipelines for model retraining and performance evaluation Required Skills Proficiency in machine learning, deep learning, and data engineering frameworks (e.g., Spark, Kafka) Hands-on experience with MLOps, including tools like Docker, Kubernetes, Kubeflow, MLflow, and TFX Expertise with major cloud platforms (AWS, GCP, Azure) In-depth understanding of model deployment, monitoring, security, compliance, and responsible AI Preferred Skills Experience with A/B testing, Bayesian optimization, and hyperparameter tuning Familiarity with generative AI workflows, such as LLM fine-tuning, FAISS, and vector databases Exposure to multi-cloud ML infrastructure setups Why Join Us Pay above market standards Flexible contract-based or freelance engagements Work remotely, onsite with clients, or from Deccan AI offices in Hyderabad/Bangalore Collaborate with elite professionals on cutting-edge AI initiatives

Join us as a Data Scientist at Barclays, where you'll take part in the evolution of our digital landscape, driving innovation and excellence You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences As a part of the Service Operations team, you will deliver technology stack, using strong analytical and problem solving skills to understand the business requirements and deliver quality solutions You'll be working on complex technical problems that will involve detailed analytical skills and analysis This will be done in conjunction with fellow engineers, business analysts and business stakeholders To be successful as a Data Scientist you should have experience with: Essential Skills Solid understanding of machine learning concepts and model deployment Prior experience in a data science role, indicating a strong foundation in the field Advanced coding proficiency in Python, with the ability to design, test, and correct complex scripts Proficiency in SQL, for managing and manipulating data Working in an Agile manner and leading Agile teams using Jira Some Other Highly Valued Skills Include Excellent modelling skills, as evidenced by an advanced degree or significant experience Strong quantitative and statistical skills, enabling logical and methodical problem-solving Good understanding and experience of big data technologies and the underlying approach Good interpersonal skills for maintaining relationships with multiple business areas, including senior leadership and compliance Ability to manage laterally and upwards across multiple discipline technical areas Version control using Bitbucket, Gitlab, etc Cloud experience (AWS, Azure or GCP) You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills This role is based in Pune Purpose of the role To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation Accountabilities Identification, collection, extraction of data from various sources, including internal and external sources Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis Development and maintenance of efficient data pipelines for automated data acquisition and processing Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness Collaborate closely with other functions/ business divisions Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard The four LEAD behaviours are: L Listen and be authentic, E Energise and inspire, A Align across the enterprise, D Develop others OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda Take ownership for managing risk and strengthening controls in relation to the work done Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc) to solve problems creatively and effectively Communicate complex information 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience Influence or convince stakeholders to achieve outcomes All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship our moral compass, helping us do what we believe is right They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge and Drive the operating manual for how we behave

What will your role look like Design, train, evaluate, and deploy traditional ML models as well as Generative AI-based applications. Work on supervised, unsupervised, and deep learning models including regression, classification, clustering, and sequence models. Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation. Develop and optimize LLM-based workflows using LangChain, LangGraph, and orchestration frameworks. Fine-tune, evaluate, and integrate LLMs such as GPT, LLaMA, Claude, Mistral, Falcon, Cohere, and Gemini. Implement Retrieval-Augmented Generation (RAG) using embeddings and vector stores like FAISS, Pinecone, or Chroma. Apply prompt engineering, LoRA, PEFT, and adapter-based fine-tuning to optimize LLMs for specific tasks. Build Agentic AI systems with tool-use capabilities and reasoning chains (e.g., ReAct, AutoGPT, BabyAGI, CrewAI). Use Hugging Face for leveraging pre-trained models and datasets for rapid experimentation. Collaborate with product, data, and engineering teams to productionize AI solutions using scalable cloud infrastructure. Why you will love this role Besides a competitive package, an open workspace full of smart and pragmatic team members, with ever-growing opportunities for professional and personal growth Be a part of a learning culture where teamwork and collaboration are encouraged, diversity is valued and excellence, compassion, openness and ownership is rewarded. We would like you to bring along Strong grasp of core ML concepts such as model selection, evaluation metrics, bias/variance tradeoff, overfitting/underfitting, etc. Good exposure on using Azure Open AI and hosting applications in Azure environment Experience in building and tuning models using scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Experience in building ML pipelines with feature engineering, model tuning, cross-validation, and A/B testing. Proficiency in LangChain, LangGraph, and integrating with Hugging Face Transformers Ecosystem. Deep knowledge of various LLMs and techniques like prompt engineering, few-shot learning, and instruction tuning. Experience in building Agentic AI systems and coordinating multi-agent flows or tool-chaining. Familiarity with LLMOps/MLOps tools (e.g., MLflow, Weights & Biases, Kubeflow, SageMaker, or Vertex AI). Strong programming skills in Python, and experience deploying models using FastAPI, Flask, or Streamlit. Experience with cloud platforms (AWS/GCP/Azure) and handling GPU/TPU resources. Solid understanding of data structures, algorithms, and software engineering best Practices. Highly skilled AI/ML Engineer with a solid foundation in Machine Learning and deep hands-on experience in Generative AI (GenAI). Strong capabilities in building, training, and deploying ML models, along with significant experience. working with frameworks such as LangChain, LangGraph, and platforms like Hugging Face, vector databases, and various LLMs. Youll be a key contributor in developing smart assistants, AI agents, and ML solutions that solve complex business problems. Experience with LangSmith, PromptLayer, or other LLM observability tools Familiarity with Guardrails.AI, semantic caching, and output validation techniques Exposure to multi-modal models like CLIP, DALLE, Stable Diffusion, or Whisper Contributions to open-source GenAI or ML libraries/projects Domain expertise in areas like healthcare, finance, manufacturing, or legal tech.

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Technical and Professional : Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Preferred Skills: Technology-Machine learning-data science Technology-Machine Learning-Python Technology-Machine Learning-Generative AI

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Technical and Professional : Technical skills ProgrammingPython, R, SQL ML algorithms Statistical ML algorithms Deep Neural Network architectures Model ensembling Generative AI models ML for Responsible AI AI domains - NLP, speech, computer vision, structured data Learning patterns – supervised, unsupervised, reinforcement learning Tools for data analysis, auto ML, model deployment & scaling, model fine tuning Knowledge of different Model fine tuning approaches for Large models Knowledge of datasets, pre-built models available in open community and 3rd party providers Knowledge of software development & architectures Knowledge of hyperscalers & their AI capabilities – Azure, AWS, GCP Knowledge of Model Quantization and Pruning Past experience playing a Data Scientist role Preferred Skills: Technology-Machine learning-data science Technology-Machine Learning-Python Technology-Machine Learning-Generative AI

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : Microsoft Azure IaaS Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. Your typical day will involve collaborating with various teams to ensure that application requirements are met, overseeing the development process, and providing guidance to team members. You will also engage in problem-solving activities, ensuring that the applications are optimized for performance and usability while maintaining effective communication with stakeholders to align on project goals and timelines. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Facilitate knowledge sharing sessions to enhance team capabilities.- Monitor project progress and ensure adherence to timelines and quality standards. Professional & Technical Skills: - Must To Have Skills: Proficiency in Microsoft Azure IaaS.- Good To Have Skills: Experience with Microsoft Azure Windows Virtual Desktop.- Strong understanding of cloud architecture and deployment models.- Experience in managing and configuring virtual machines and networks in Azure.- Familiarity with automation tools and scripting for Azure management. Additional Information:- The candidate should have minimum 5 years of experience in Microsoft Azure IaaS.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Key Responsibilities. Architect, build, and deploy AI/ML models for SaaS products at scale.. Lead the end-to-end lifecycle of AI projects from data exploration, model development, validation, and deployment, to monitoring and maintenance.. Collaborate with Product Management, Engineering, and Design teams to integrate AI capabilities into product offerings.. Implement and optimize Retrieval Augmented Generation (RAG) systems, Large Language Models (LLMs), and other emerging AI/ML techniques.. Define and uphold best practices in AI model development, MLOps, and scalable deployment.. Mentor and guide a team of AI/ML engineers, setting technical direction and fostering a culture of innovation and excellence.. Partner with stakeholders to define AI strategies aligned with overall technology roadmaps and business objectives.. Stay abreast of advancements in AI and contribute thought leadership internally and externally.. Required Skills & Experience. 10 to12 years of experience in AI/ML engineering, with a strong record of working in SaaS and product-based environments.. Expertise in Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and/or Generative AI.. Hands-on experience with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc.. Solid experience in designing scalable AI architectures and deploying models in production environments (AWS, GCP, Azure, etc.. Strong programming skills in Python; familiarity with other languages like Java, Go, or Scala is a plus.. Deep understanding of MLOps, CI/CD for machine learning pipelines, containerization (Docker, Kubernetes).. Experience with LLM fine-tuning, prompt engineering, vector databases (e., Pinecone, FAISS) is highly desirable.. Has experience is having trained a SLM (or Medium Language Model), for a particular vertical.. This includes pre-training and fine-tuning.. Strong problem-solving skills and ability to navigate ambiguous technical challenges.. Excellent communication, leadership, and stakeholder management skills.. Preferred Qualifications. Master's or Ph.in Computer Science, Machine Learning, Data Science, or a related field.. Experience in Go-to-Market Strategy for AI-powered products.. Experience integrating AI into customer-facing SaaS products with measurable outcomes..

Project Role : Cloud Migration Engineer Project Role Description : Provides assessment of existing solutions and infrastructure to migrate to the cloud. Plan, deliver, and implement application and data migration with scalable, high-performance solutions using private and public cloud technologies driving next-generation business outcomes. Must have skills : Cloud Migration Planning Good to have skills : Microsoft Azure IaaS, VMWare Cloud AdministrationMinimum 7.5 year(s) of experience is required Educational Qualification : Graduate Post Graduate BE B Tech MSC IT M Tech M Sc CS Summary :As a Cloud Migration Engineer, you will provide a comprehensive assessment of existing solutions and infrastructure to facilitate their migration to the cloud. Your typical day will involve planning, delivering, and implementing application and data migration strategies that leverage both private and public cloud technologies. You will focus on creating scalable and high-performance solutions that drive next-generation business outcomes, ensuring that the migration process aligns with organizational goals and enhances operational efficiency. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Develop and maintain comprehensive migration plans that outline timelines, resources, and risk management strategies.- Facilitate training and knowledge transfer sessions to ensure team members are equipped with the necessary skills for cloud technologies. Professional & Technical Skills: - Must To Have Skills: Proficiency in Cloud Migration Planning.- Good To Have Skills: Experience with Microsoft Azure IaaS, VMWare Cloud Administration.- Strong understanding of cloud architecture and deployment models.- Experience with data migration tools and techniques.- Familiarity with security best practices in cloud environments. Additional Information:- The candidate should have minimum 7.5 years of experience in Cloud Migration Planning.- This position is based at our Bengaluru office.- A Graduate Post Graduate BE B Tech MSC IT M Tech M Sc CS is required. Qualification Graduate Post Graduate BE B Tech MSC IT M Tech M Sc CS

Step into the world of AI innovation with the Experts Community of Soul AI (By Deccan AI). We are looking for Indias top 1% Machine Learning 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 Machine Learning Engineers with expertise in building, deploying, and optimizing AI models. 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 2-6 months, or freelancing. Be a part of Elite Community of professionals who can solve complex AI challenges. Work location could be:. Remote (Most likely). Onsite on client location. Deccan AIs OfficeHyderabad or Bangalore. Responsibilities:. Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines. Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes). Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations. Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking. Required Skills: . Proficiency in machine learning, deep learning, and data engineering (Spark, Kafka). Expertise in MLOps, automation tools (Docker, Kubernetes, Kubeflow, MLflow, TFX), and cloud platforms (AWS, GCP, Azure). Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices. Nice to Have:. Experience with A/B testing, Bayesian optimization, and hyperparameter tuning. Familiarity with multi-cloud ML deployments and generative AI technologies (LLM fine-tuning, FAISS). What are the next steps. Register on our Soul AI website. Our team will review your profile. Clear all the screening roundsClear the assessments once you are shortlisted. Profile matching and Project AllocationBe patient while we align your skills and preferences with the available project. Skip the Noise. Focus on Opportunities Built for You!.

Step into the world of AI innovation with the Experts Community of Soul AI (By Deccan AI). We are looking for Indias top 1% Machine Learning 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 Machine Learning Engineers with expertise in building, deploying, and optimizing AI models. 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 2-6 months, or freelancing. Be a part of Elite Community of professionals who can solve complex AI challenges. Work location could be:. Remote (Most likely). Onsite on client location. Deccan AIs OfficeHyderabad or Bangalore. Responsibilities:. Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines. Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes). Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations. Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking. Required Skills: . Proficiency in machine learning, deep learning, and data engineering (Spark, Kafka). Expertise in MLOps, automation tools (Docker, Kubernetes, Kubeflow, MLflow, TFX), and cloud platforms (AWS, GCP, Azure). Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices. Nice to Have:. Experience with A/B testing, Bayesian optimization, and hyperparameter tuning. Familiarity with multi-cloud ML deployments and generative AI technologies (LLM fine-tuning, FAISS). What are the next steps. Register on our Soul AI website. Our team will review your profile. Clear all the screening roundsClear the assessments once you are shortlisted. Profile matching and Project AllocationBe patient while we align your skills and preferences with the available project. Skip the Noise. Focus on Opportunities Built for You!.

Step into the world of AI innovation with the Experts Community of Soul AI (By Deccan AI). We are looking for Indias top 1% Machine Learning 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 Machine Learning Engineers with expertise in building, deploying, and optimizing AI models. 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 2-6 months, or freelancing. Be a part of Elite Community of professionals who can solve complex AI challenges. Work location could be:. Remote (Most likely). Onsite on client location. Deccan AIs OfficeHyderabad or Bangalore. Responsibilities:. Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines. Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes). Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations. Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking. Required Skills: . Proficiency in machine learning, deep learning, and data engineering (Spark, Kafka). Expertise in MLOps, automation tools (Docker, Kubernetes, Kubeflow, MLflow, TFX), and cloud platforms (AWS, GCP, Azure). Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices. Nice to Have:. Experience with A/B testing, Bayesian optimization, and hyperparameter tuning. Familiarity with multi-cloud ML deployments and generative AI technologies (LLM fine-tuning, FAISS). What are the next steps. Register on our Soul AI website. Our team will review your profile. Clear all the screening roundsClear the assessments once you are shortlisted. Profile matching and Project AllocationBe patient while we align your skills and preferences with the available project. Skip the Noise. Focus on Opportunities Built for You!.

Step into the world of AI innovation with the Experts Community of Soul AI (By Deccan AI). We are looking for Indias top 1% Machine Learning 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 Machine Learning Engineers with expertise in building, deploying, and optimizing AI models. 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 2-6 months, or freelancing. Be a part of Elite Community of professionals who can solve complex AI challenges. Work location could be:. Remote (Most likely). Onsite on client location. Deccan AIs OfficeHyderabad or Bangalore. Responsibilities:. Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines. Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes). Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations. Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking. Required Skills: . Proficiency in machine learning, deep learning, and data engineering (Spark, Kafka). Expertise in MLOps, automation tools (Docker, Kubernetes, Kubeflow, MLflow, TFX), and cloud platforms (AWS, GCP, Azure). Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices. Nice to Have:. Experience with A/B testing, Bayesian optimization, and hyperparameter tuning. Familiarity with multi-cloud ML deployments and generative AI technologies (LLM fine-tuning, FAISS). What are the next steps. Register on our Soul AI website. Our team will review your profile. Clear all the screening roundsClear the assessments once you are shortlisted. Profile matching and Project AllocationBe patient while we align your skills and preferences with the available project. Skip the Noise. Focus on Opportunities Built for You!.

Looking for Generative AI, NLP, and Deep Learning.Proficient in PyTorch, Python & Prompt Engineering.Hands-on exp. with LLM fine-tuning & GPU acceleration.Previous exp. deploying AI models on the cloud. Candidates from IITs/NITs are highly preferred

Management Level :07 - Manager Location :Gurgaon/Bangalore/Mumbai Must have skills :Python Programming, Machine Learning, Generative AI (GPT, DALLE, GANs), Model Deployment, Cloud (AWS/Azure/GCP), Statistical Analysis, Data Science, API Development, Docker/Kubernetes Good to have skills :PyTorch, TensorFlow, NLP, Computer Vision, Performance Optimization, Ethical AI Practices, Cloud Integrations, Open-Source Contributions Job Summary : Accenture AI is seeking a talented and motivated Generative AI Data Scientist Lead to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis and Cloud Platforms to drive and lead the development & delivery of the innovative solutions and enhance our AI capabilities. This role will involve collaborating with cross-functional teams to design, develop, and implement generative AI solutions that meet our business needs. Roles & Responsibilities: Independent Project Leadership :Take ownership of end-to-end project delivery, from problem definition to solution deployment, with minimal supervision. Pod Leadership :Lead and mentor a small development pod (team) of data scientists and engineers, ensuring collaboration, innovation, and timely delivery of high-quality solutions. Model Development :Design, develop, and deploy state-of-the-art generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for applications such as text generation, image synthesis, content creation, and more. Strategy Development :Provide strategic recommendations to clients on how to integrate generative AI into their workflows and business processes. Ethical AI Practices :Ensure responsible use of generative AI by addressing biases, ethical concerns, and compliance with regulations. Performance Evaluation :Develop evaluation metrics and methodologies to assess the performance of generative models and ensure they meet quality standards. Collaboration :Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Research and Innovation :Stay up-to-date with the latest advancements in generative AI and machine learning, applying that knowledge to improve existing models and techniques. Mentorship :Guide and mentor junior team members, fostering a culture of innovation and continuous learning. Professional & Technical Skills: 6+ years of experience in Data Science , Machine Learning , or related fields with a focus on Generative AI models (LLMs) . Expert proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow , PyTorch ). Hands-on experience with cloud platforms (AWS, GCP, Azure), including deployment and solution building . Ability to work with Docker , Kubernetes , and API Development to deploy generative AI models. Strong analytical, problem-solving , and critical thinking skills. Expertise in ethical AI practices and understanding of the biases and regulations surrounding Generative AI . Excellent verbal and written communication skills, with the ability to clearly convey complex concepts to diverse audiences. Additional Information: Experience with large-scale data processing and cloud computing platforms. Familiarity with NLP , computer vision , and other AI applications. Publications or contributions to open-source AI/ML projects . Experience in cloud integrations and performance optimization . Strong leadership skills with experience in guiding teams and managing AI projects. About Our Company | AccentureQualification Experience :Minimum 6+ years of experience in Data Science, Machine Learning, or a related field with a focus on Generative AI models (LLMs) and leadership in AI solutions. Educational Qualification :Masters or Ph.D. in Computer Science , Data Science , Statistics , or related field.

Dear Candidate, We are seeking a Machine Learning Engineer to develop predictive models and deploy them into production. Ideal for professionals passionate about AI and data science. Key Responsibilities: Develop and train machine learning models Preprocess and analyze large datasets Deploy models using scalable infrastructure Collaborate with product teams to integrate ML solutions Required Skills & Qualifications: Strong knowledge of Python and ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with data preprocessing and feature engineering Familiarity with model deployment techniques Bonus: Experience with cloud ML services (AWS SageMaker, Google AI Platform) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

We are looking for experienced ML Ops Engineer with 3+ years of experience, specializing in Machine Learning. In this role, you will be responsible for developing ML infrastructure around LLMs/ML Models. The ideal candidate will possess a deep understanding of the ML lifecycle and infrastructure. Key Responsibilities: Collaboration: Work closely with data scientists and ML engineers throughout the ML lifecycle, supporting model development, deployment, and monitoring. ML Ops Pipeline Development: Design, implement, and optimize ML Ops pipelines using tools and frameworks such as TensorFlow Serving, Kubeflow, MLflow, or similar technologies. Data Pipeline Engineering: Build and maintain data pipelines and infrastructure necessary for enterprise-scale machine learning applications, focusing on tasks like data ingestion, preprocessing, transformation, feature engineering, and model training. Cloud Implementation: Develop cloud-based ML Ops solutions on cloud platforms like AWS, Azure, GCP. Containerization Skills: Familiarity with containerization technologies like Docker and Kubernetes. Model Deployment and Monitoring: Deploy and monitor various machine learning models in production, including text/NLP and generative AI models. CI/CD Automation: Build and maintain CI/CD pipelines using tools such as GitLab CI, GitHub Actions, or Airflow to streamline the ML lifecycle. Model Review and Quality Assurance: Participate in data science model reviews, focusing on code optimization, containerization, deployment, versioning, and quality monitoring. Support Data Model Development: Contribute to data model development with an emphasis on auditability, versioning, and data security, implementing practices like lineage tracking and model explainability. Mentorship: Provide guidance and support to junior engineers, fostering a collaborative and innovative team environment. Experience: Minimum of 3+ years of relevant work experience in ML Ops. Domain Knowledge: Strong expertise in Generative AI, advanced NLP, and machine learning techniques. Production Experience: Proven experience in deploying and maintaining production-grade AI solutions. Communication Skills: Excellent communication and teamwork skills, with the ability to work independently when needed. Problem-Solving: Strong analytical and problem-solving capabilities. Continuous Learning: Stay informed about the latest advancements in ML Ops technologies and actively explore new tools and techniques to improve system performance and reliability.

Were looking for a passionate AI/ML Engineer with 02 years of experience whos eager to dive deep into document processing, computer vision, and real-world AI problems. This role is ideal for someone who wants to grow with a startup and experience the complete journey of building and scaling intelligent systems. Key Responsibilities Assist in selecting, adapting, and implementing AI models for document parsing, table detection, layout analysis, and OCR enhancement. Fine-tune and optimize models such as Detectron2, LayoutLM, Donut, YOLO , or similar vision transformers. Apply model compression techniques like quantization , pruning , and ONNX for faster deployment. Contribute to integrating AI pipelines into production-grade backend systems. Collaborate with product and engineering teams to continuously improve output quality. Explore recent research in document intelligence and suggest innovations. Required Skills Proficiency in Python and libraries such as PyTorch or TensorFlow. Understanding of AI model training and evaluation workflows. Hands-on with at least one of: object detection models (YOLO, Detectron2), layout models (LayoutLM, Donut), or image preprocessing. Strong analytical skills and a hunger to learn. Preferred Qualities Prior internship or personal projects in Computer Vision or Document AI. Familiarity with OCR tools like Tesseract, EasyOCR, or Azure/GCP Vision APIs. Exposure to model deployment (ONNX/TensorRT, Docker, API development). Preference will be given to candidates who are enthusiastic about working in a startup and want to experience the journey of building and scaling AI products from the ground up. Why Join Us? Be part of a fast-growing AI startup solving meaningful real-world problems. Work directly with founders, senior engineers, and real customers. Fast-paced learning environment with end-to-end ownership. Flexible work hours and open culture.