69 Deploying Models Jobs - Page 2

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.

4+ years of Anaplan model building experience (Anaplan L3 or Solution Architect Certification) Strong technical background in consulting, finance, or software implementation. Expertise in building, troubleshooting complex multidimensional models. Required Candidate profile Exp in stakeholder management. Knowledge of data architecture, cross-platform integration. Exp in Anaplan FP&A Implementation. Strong Communication Skills Apply on - thak.priyanka@exponent.com.sg

Role & responsibilities Design machine learning systems Research and implement machine learning algorithms and tools Manage and direct research and development processes to meet the needs of our AI strategy Develop machine learning applications in alignment with project requirements and business goals Perform machine learning tests and statistical analysis in order to fine-tune the machine learning systems Select appropriate datasets and data representation methods Extend existing machine learning libraries and frameworks Train systems and retrain as necessary Work with the engineering and leadership teams on the functional design, process design, prototyping, testing, and training of AI/ML solutions Advise leaders on technology, strategy, and policy issues related to AI/ML AI and computer science more broadly can be seen as a way of solving problems. From small ones such as which piece of code to feed into an AI, to finding automated solutions to global education or health issues . No matter what career route you choose, developing an analytical mind will take you far in Artificial Intelligence and honing those skills will take practice. Throughout the course you’ll be encouraged to do just that. During your dissertation project you’ll have the opportunity to apply your knowledge and improve your problem solving capabilities during a substantial piece of independent research. Preferred candidate profile Knowledge of basic algorithms and object-oriented and functional design principles Knowledge of data structures, data modeling, and software architecture Knowledge of math, probability, statistics, and algorithms Knowledge of machine learning frameworks such as Keras and PyTorch Knowledge of machine learning libraries such as scikit-learn

Purpose Of The Position: We are looking for a highly experienced Senior Data Scientist with a deep understanding of AI/ML technologies, including Recommendation Systems, Chatbots, Generative AI, and Large Language Models (LLMs). The ideal candidate will have hands-on experience in applying these technologies to solve real-world problems, working with large datasets, and collaborating with cross-functional teams to deliver innovative data-driven solutions.. Key Responsibilities : Design, develop, and optimize recommendation systems to enhance user experience and engagement across platforms. Build and deploy chatbots with advanced NLP capabilities for automating customer interactions and improving business processes. Lead the development of Generative AI solutions, including content generation and automation. Research and apply Large Language Models (LLMs) like GPT, BERT, and others to solve business-specific problems and create innovative solutions. Collaborate with engineering teams to integrate machine learning models into production systems, ensuring scalability and reliability. Perform data exploration, analysis, and feature engineering to improve model performance. Stay updated on the latest advancements in AI and ML technologies, proposing new techniques and tools to enhance our product capabilities. Mentor junior data scientists and engineers, providing guidance on best practices in AI/ML model development and deployment. Collaborate with product managers and business stakeholders to translate business goals into AI-driven solutions. Work on model interpretability, explainability, and ensure models are built in an ethical and responsible manner. Required Skills And Qualifications: 5+ years of experience in data science or machine learning, with a focus on building and deploying AI models. Strong expertise in designing and developing recommendation systems and working with collaborative filtering, matrix factorization, and content-based filtering techniques. Hands-on experience with chatbots using Natural Language Processing (NLP) and conversational AI frameworks. In-depth understanding of Generative AI, including transformer-based models and GANs (Generative Adversarial Networks). Experience working with Large Language Models (LLMs) such as GPT, BERT, T5, etc. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn. Strong programming skills in Python and libraries such as NumPy, Pandas, Hugging Face, and NLTK. Experience with cloud platforms like AWS, GCP, or Azure for deploying and scaling machine learning models. Solid understanding of data pipelines, ETL processes, and working with large datasets using SQL or NoSQL databases. Knowledge of MLOps and experience deploying models in production environments. Strong problem-solving skills and a deep understanding of statistical methods and algorithms. Preferred Qualifications: Experience with Reinforcement Learning and Recommender Systems personalization techniques. Experience of working with AWS Bedrock services. Familiarity with ethical AI and model bias mitigation techniques. Experience with A/B testing, experimentation, and performance tracking for AI models in production. Prior experience mentoring junior data scientists and leading AI/ML projects. Strong communication and collaboration skills, with the ability to convey complex technical concepts to non-technical stakeholders. Why Join Us? Opportunity to be part of a rapidly growing, innovative product-based company. Collaborate with a talented, driven team focused on building high-quality software solutions. Competitive compensation and benefits package.

job requisition idJR1027361 Job Summary Synechron seeks a highly skilled AI/ML Engineer specializing in Natural Language Processing (NLP), Large Language Models (LLMs), Foundation Models (FMs), and Generative AI (GenAI). The successful candidate will design, develop, and deploy advanced AI solutions, contributing to innovative projects that transform monolithic systems into scalable microservices integrated with leading cloud platforms such as Azure, Amazon Bedrock, and Google Gemini. This role plays a critical part in advancing Synechrons capabilities in cutting-edge AI technologies, enabling impactful business insights and product innovations. Software Required Proficiency: Python (core librariesTensorFlow, PyTorch, Hugging Face transformers, etc.) Cloud platformsAzure, AWS, Google Cloud (familiarity with AI/ML services) ContainerizationDocker, Kubernetes Version controlGit Data management toolsSQL, NoSQL databases (e.g., MongoDB) Model deployment and MLOps toolsMLflow, CI/CD pipelines, monitoring tools Preferred Skills: Experience with cloud-native AI frameworks and SDKs Familiarity with AutoML tools Additional programming languages (e.g., Java, Scala) Overall Responsibilities Design, develop, and optimize NLP models, including advanced LLMs and Foundation Models, for diverse business use cases. Lead the development of large data pipelines for training, fine-tuning, and deploying models on big data platforms. Architect, implement, and maintain scalable AI solutions in line with MLOps best practices. Transition legacy monolithic AI systems into modular, microservices-based architectures for scalability and maintainability. Build end-to-end AI applications from scratch, including data ingestion, model training, deployment, and integration. Implement retrieval-augmented generation techniques for enhanced context understanding and response accuracy. Conduct thorough testing, validation, and debugging of AI/ML models and pipelines. Collaborate with cross-functional teams to embed AI capabilities into customer-facing and enterprise products. Support ongoing maintenance, monitoring, and scaling of deployed AI systems. Document system designs, workflows, and deployment procedures for compliance and knowledge sharing. Performance Outcomes: Production-ready AI solutions delivering high accuracy and efficiency. Robust data pipelines supporting training and inference at scale. Seamless integration of AI models with cloud infrastructure. Effective collaboration leading to innovative AI product deployment. Technical Skills (By Category) Programming Languages: Essential: Python (TensorFlow, PyTorch, Hugging Face, etc.) Preferred: Java, Scala Databases/Data Management: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB) Cloud Technologies: Azure AI, AWS SageMaker, Bedrock, Google Cloud Vertex AI, Gemini Frameworks and Libraries: Transformers, Keras, scikit-learn, XGBoost, Hugging Face engines Development Tools & Methodologies: Docker, Kubernetes, Git, CI/CD pipelines (Jenkins, Azure DevOps) Security & Compliance: Knowledge of data security standards and privacy policies (GDPR, HIPAA as applicable) Experience 8 to 10 years of hands-on experience in AI/ML development, especially NLP and Generative AI. Demonstrated expertise in designing, fine-tuning, and deploying LLMs, FMs, and GenAI solutions. Proven ability to develop end-to-end AI applications within cloud environments. Experience transforming monolithic architectures into scalable microservices. Strong background with big data processing pipelines. Prior experience working with cloud-native AI tools and frameworks. Industry experience in finance, healthcare, or technology sectors is advantageous. Alternative Experience: Candidates with extensive research or academic experience in AI/ML, especially in NLP and large-scale data processing, are eligible if they have practical deployment experience. Day-to-Day Activities Develop and optimize sophisticated NLP/GenAI models fulfilling business requirements. Lead data pipeline construction for training and inference workflows. Collaborate with data engineers, architects, and product teams to ensure scalable deployment. Conduct model testing, validation, and performance tuning. Implement and monitor model deployment pipelines, troubleshoot issues, and improve system robustness. Document models, pipelines, and deployment procedures for audit and knowledge sharing. Stay updated with emerging AI/ML trends, integrating best practices into projects. Present findings, progress updates, and technical guidance to stakeholders. Qualifications Bachelors degree in Computer Science, Data Science, or related field; Masters or PhD preferred. Certifications in AI/ML, Cloud (e.g., AWS, Azure, Google Cloud), or Data Engineering are a plus. Proven professional experience with advanced NLP and Generative AI solutions. Commitment to continuous learning to keep pace with rapidly evolving AI technologies. Professional Competencies Strong analytical and problem-solving capabilities. Excellent communication skills, capable of translating complex technical concepts. Collaborative team player with experience working across global teams. Adaptability to rapidly changing project scopes and emerging AI trends. Innovation-driven mindset with a focus on delivering impactful solutions. Time management skills to prioritize and manage multiple projects effectively.

job requisition idJR1027352 Job Summary Synechron is seeking an analytical and innovative Senior Data Scientist to support and advance our data-driven initiatives. The ideal candidate will have a solid understanding of data science principles, hands-on experience with AI/ML tools and techniques, and the ability to interpret complex data sets to deliver actionable insights. This role contributes to the organizations strategic decision-making and technology innovation by applying advanced analytics and machine learning models in a collaborative environment. Software Required Skills: Python (including libraries such as pandas, scikit-learn, TensorFlow, PyTorch) proficiency in developing and deploying models R (optional, but preferred) Data management tools (SQL, NoSQL databases) Cloud platforms (preferably AWS or Azure) for data storage and ML deployment Jupyter Notebooks or similar interactive development environments Version control tools such as Git Preferred Skills: Big data technologies (Spark, Hadoop) Model deployment tools (MLflow, Docker, Kubernetes) Data visualization tools (Tableau, Power BI) Overall Responsibilities Analyze and interpret large and complex data sets to generate insights for business and technology initiatives. Assist in designing, developing, and implementing AI/ML models and algorithms to solve real-world problems. Collaborate with cross-functional teams including data engineers, software developers, and business analysts to integrate models into production systems. Stay current with emerging trends, research, and best practices in AI/ML/Data Science and apply them to ongoing projects. Document methodologies, modeling approaches, and insights clearly for technical and non-technical stakeholders. Support model validation, testing, and performance monitoring to ensure accuracy and reliability. Contribute to the development of data science workflows and standards within the organization. Performance Outcomes: Accurate and reliable data models that support strategic decision-making. Clear documentation and communication of findings and recommendations. Effective collaboration with technical teams to deploy scalable models. Continuous adoption of best practices in AI/ML and data management. Technical Skills (By Category) Programming Languages: Essential: Python (best practices in ML development), SQL Preferred: R, Java (for integration purposes) Databases/Data Management: SQL databases, NoSQL (MongoDB, Cassandra) Cloud data storage solutions (AWS S3, Azure Blob Storage) Cloud Technologies: AWS (S3, EC2, SageMaker, Lambda) Azure Machine Learning (preferred) Frameworks & Libraries: TensorFlow, PyTorch, scikit-learn, Keras, XGBoost Development Tools & Methodologies: Jupyter Notebooks, Git, CI/CD pipelines Agile and Scrum processes Security Protocols: Best practices in data security and privacy, GDPR compliance Experience 8+ years of professional experience in AI, ML, or Data Science roles. Proven hands-on experience designing and deploying ML models in real-world scenarios. Demonstrated ability to analyze complex data sets and translate findings into business insights. Previous experience working with cloud-based data science solutions is preferred. Strong portfolio showcasing data science projects, models developed, and practical impact. Alternative Pathways: Candidates with extensive research or academic experience in AI/ML can be considered, provided they demonstrate practical application of skills. Day-to-Day Activities Conduct data exploration, cleaning, feature engineering, and model development. Collaborate with data engineers to prepare data pipelines for model training. Build, validate, and refine machine learning models. Present insights, models, and recommendations to technical and business stakeholders. Support deployment of models into production environments. Monitor model performance and iterate to improve effectiveness. Participate in team meetings, project planning, and reviewing progress. Document methodologies and maintain version control of codebase. Qualifications Bachelors degree in Computer Science, Mathematics, Statistics, Data Science, or a related field; Masters or PhD highly desirable. Evidence of relevant coursework, certifications, or professional training in AI/ML. Professional certifications (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified Data Scientist) are a plus. Commitment to ongoing professional development in AI/ML methodologies. Professional Competencies Strong analytical and critical thinking to solve complex problems. Effective communication skills for technical and non-technical audiences. Demonstrated ability to work collaboratively in diverse teams. Aptitude for learning new tools, techniques, and technologies rapidly. Innovation mindset with a focus on applying emerging research. Strong organizational skills to manage multiple projects and priorities.

Project Role : Software Development Lead Project Role Description : Develop and configure software systems either end-to-end or for a specific stage of product lifecycle. Apply knowledge of technologies, applications, methodologies, processes and tools to support a client, project or entity. Must have skills : Oracle Cloud Infrastructure Administration Good to have skills : Oracle Advanced Access ControlsMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Software Development Lead, you will engage in the development and configuration of software systems, either managing the entire process or focusing on specific stages of the product lifecycle. Your day will involve applying your extensive knowledge of various technologies, applications, methodologies, and tools to effectively support clients and projects, ensuring that all systems are optimized for performance and functionality. You will also collaborate with team members to address challenges and implement innovative solutions that enhance the overall project outcomes. 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.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing and mentoring within the team to enhance overall skill levels.- Monitor project progress and ensure alignment with strategic goals. Professional & Technical Skills: - Must To Have Skills: Proficiency in Oracle Cloud Infrastructure Administration.- Strong understanding of cloud architecture and deployment models.- Experience with infrastructure as code tools such as Terraform or Ansible.- Familiarity with security best practices in cloud environments.- Ability to troubleshoot and optimize cloud-based applications. Additional Information:- The candidate should have minimum 12 years of experience in Oracle Cloud Infrastructure Administration.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Role Overview : Hiring an ML Engineer with experience in Cloudera ML to support end-to-end model development, deployment, and monitoring on the CDP platform. Key Responsibilities : Develop and deploy models using CML workspaces Build CI/CD pipelines for ML lifecycle Integrate with governance and monitoring tools Enable secure model serving via REST APIs Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required : Experience in Cloudera ML, Spark MLlib, or scikit-learn ML pipeline automation (MLflow, Airflow, or equivalent) Model governance, lineage, and versioning API exposure for real-time inference