39 Deploying Models Jobs - Page 2

Management Level :09 - Senior Consultant Location :Gurgaon/Bangalore/Mumbai Must have skills :Python Programming, Machine Learning, Statistical Analysis, Data Science, Generative AI (GPT, DALLE, GANs), Cloud (AWS/Azure/GCP), Model Deployment, API Development, Docker/Kubernetes Good to have skills :PyTorch, TensorFlow, Large-Scale Data Processing, Cloud Integrations, NLP, Computer Vision, Security Best Practices, Performance Optimization, Open-Source Contributions Job Summary : Accenture AI is seeking a talented and motivated Generative AI Data Scientist Consultant to join our Banking team. The ideal candidate will leverage their expertise in Generative AI models, Machine Learning, Data Analysis, and Cloud Platforms to develop innovative solutions and enhance 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: Collaboration :Work closely with product managers, engineers, and other stakeholders to understand requirements and deliver impactful AI solutions. Model Deployment :Containerize and deploy generative AI models using tools like Docker, Kubernetes, and cloud platforms (e.g., AWS, Azure, Google Cloud). API Development :Design, develop, and deploy robust APIs to expose generative AI models (e.g., GPT, DALLE, Stable Diffusion, GANs) for integration into client systems and applications. Client Collaboration :Work closely with clients to understand their technical requirements and deliver tailored API solutions that meet their business needs. Generative AI Model Integration :Integrate generative AI models into existing workflows, applications, and platforms via APIs. Performance Optimization :Optimize API performance for latency, scalability, and reliability, ensuring seamless user experiences. Data Pipeline Development :Build and maintain data pipelines to support real-time or batch processing for generative AI models. Security and Compliance :Implement security best practices and ensure APIs comply with data privacy and regulatory standards. Documentation :Create comprehensive API documentation, including usage examples, SDKs, and troubleshooting guides. Testing and Monitoring :Develop automated testing frameworks and monitoring systems to ensure API reliability and performance. Stay Updated :Keep up with the latest advancements in generative AI, API development, and cloud technologies to bring innovative solutions to clients. Professional & Technical Skills: 3+ years of experience in Data Science and Machine Learning with a focus on Generative AI models (LLMs). Strong proficiency in Python programming and experience with machine learning frameworks (e.g., TensorFlow, PyTorch ). Expertise in API Development and deployment, with hands-on experience with Docker , Kubernetes , and cloud platforms (AWS, GCP, Azure). Ability to build and optimize data pipelines for generative AI models. Knowledge of security best practices and ensuring compliance with regulatory standards. Strong problem-solving, analytical, and creative thinking skills to design and implement innovative solutions. Excellent communication skills, capable of conveying complex technical concepts to diverse audiences. Additional Information: Experience with large-scale data processing and expertise in NLP or computer vision . Contributions to open-source AI/ML projects . Experience with cloud integrations , big data technologies , and performance optimization . Familiarity with security standards and regulatory compliance in AI solutions. Qualifications Experience :Minimum 3+ years of experience in Data Science, Machine Learning, or related fields with a focus on Generative AI models (LLMs) and API development . Educational Qualification :Bachelors or Masters in Computer Science, Data Science, Statistics, Engineering, or related Analytics discipline from a premier institute.

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. Qualifications 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.

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. Qualifications 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.

We are looking for a Machine Learning Engineer with expertise in MLOps to develop, deploy, and maintain scalable AI/ML pipelines . This role requires a strong background in machine learning, model deployment, cloud platforms, and automation to ensure seamless integration of AI models into production systems. You will work closely with data scientists, engineers, and DevOps teams to optimize model performance and reliability. Key Responsibilities Model Development & Deployment Design, build, and deploy scalable and efficient ML models for production use. Implement CI/CD pipelines for ML workflows using GitHub Actions, Jenkins, or GitLab CI/CD . Optimize model inference using ONNX, TensorRT, or TorchScript for faster deployment. Work with MLOps tools like MLflow, Kubeflow, TFX, and SageMaker . MLOps & Model Monitoring Develop and maintain end-to-end ML pipelines , including data ingestion, preprocessing, training, and deployment. Implement model versioning, monitoring, and retraining strategies . Set up automated model performance tracking and real-time anomaly detection using Prometheus, Grafana, or Weights & Biases. Cloud & Infrastructure Deploy models on AWS, GCP, or Azure using services like SageMaker, Vertex AI, or Azure ML . Work with containerization (Docker, Kubernetes) for model serving. Manage serverless AI deployments using Lambda, Cloud Run, or Azure Functions . Collaboration & Best Practices Work with data scientists, software engineers, and DevOps teams to optimize model integration. Establish MLOps best practices , including feature stores, automated testing, and data versioning . Ensure compliance with AI governance, model explainability, and security best practices . Qualifications & Experience Education: Bachelor's/Master's in Computer Science, AI/ML, Data Engineering, or a related field . Experience: 5-8 years in ML engineering, model deployment, and MLOps . Technical Expertise: Strong Python skills ( FastAPI, Flask, PyTorch, TensorFlow, Scikit-learn ). Experience with Kubernetes, Docker, Terraform, and cloud-based AI services . Knowledge of vector databases (FAISS, Pinecone), data pipelines (Airflow, Prefect), and streaming (Kafka, Spark Streaming) . Soft Skills: Strong problem-solving and debugging skills. Ability to work in cross-functional teams and handle production ML challenges. Strong communication and documentation abilities. Nice-to-Have: Experience with Generative AI and LLMOps (e.g., Hugging Face, LangChain, LlamaIndex). Background in edge AI deployments or real-time AI applications . Contributions to open-source AI/ML projects . Required Skills MLops, Model Deployment, Model Monitoring, Model Fine tuning, Sagemaker, Vertex

Job Title AI/ML 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->Artificial Intelligence->Artificial Intelligence - ALL Educational Requirements Bachelor of Engineering Service Line Quality * Location of posting is subject to business requirements

Short Description: Strategy and Enterprise Analytics Team provides insights and decision support tools to a broad range of business partners in sustainability and Eelectric vehicles. We drive to deliver the most value to Ford through critical thinking, AI/ML, big data analytics and optimization techniques on Google Cloud Platform (GCP). We are looking for a manager / product owner to lead a multi-skill team of data scientists, data engineers and software engineers in all phases of ongoing and future analytics services and product development, including problem formulation, data identification, model development, validation, and product launch. Description: Strategy and Enterprise Analytics Team provides insights and decision support tools to a broad range of business partners in sustainability and Eelectric vehicles. We drive to deliver the most value to Ford through critical thinking, AI/ML, big data analytics and optimization techniques on Google Cloud Platform (GCP). The team leverages advanced analytics and domain knowledge to develop analytics models, transformational decision-support tools, and services to: Increase profit while meeting North American regulatory compliance. Support strategic initiatives for electrification, especially in public charging, home power management, and energy services. Design and build solutions that support holistic decision making at enterprise level (OGC) We are looking for a manager / product owner to lead a multi-skill team of data scientists, data engineers and software engineers in all phases of ongoing and future analytics services and product development, including problem formulation, data identification, model development, validation, and product launch. The candidate should have great independence, exceptional collaboration and leadership skills, and self-discipline to guide original applied research and choose appropriate methodologies to solve related problems. We are especially excited about candidates with supervisory experience, passion for hands-on work, strong technical skills and growth mindset who demonstrate a passion for developing talents and applying state-of-the-art solutions to novel and challenging problems. Our team utilizes a diverse set of tools and methodologies from different technical fields including Machine Learning, Statistical Analysis, Simulation, Big Data platforms and more. We understand that you cannot be an expert in everything, and the set of techniques and technologies we are using today may change over time. Given the required qualifications, we are looking for candidates who are lifelong learners, driven, and curious. Responsibilities: Lead a group of data scientists, data engineers, and software engineers, to solve exciting and meaningful problems. Translate business needs into analytical problems, work hands-on along with the team, judge among candidate ML models, contribute towards best practices in model development, conduct code reviews, research state-of-the art techniques and apply them for the team and business needs. Develop and apply analytical solutions to address real-world automotive and Quality challenges. Initiate and manage cross-functional projects, building relationships with business partners, and influencing decision makers. Ability to work well under limited supervision and use good judgment to know when to update and seek guidance from leadership. Communicate and present insights to business customers and executives. Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results. Explore emerging technologies and analytic solutions for use in quantitative model development. Develop and sustain a highly performing team. Ability to collaborate, negotiate, and work effectively with coworkers at all levels. Works with Product Line Owner on creating demand and aligning the requirements to the Business demands. Qualifications: Masters degree in engineering, Data Science, Computer Science, Statistics, Industrial Engineering, or other data-related fields 5+ years of domain experience in delivering analytics solutions in any of these areas (Sustainability / Regulatory, Electrification, Legal, Cycle Planning) 10+ years of experience in analytics domain with 3+ years of supervisory experience Familiarity with SQL, Spark, Hive, and other big data technologies Familiarity with Google Cloud Platform, Python, Spark, Dataflow, BigQuery, GitHub, Qlik Sense, CPLEX, Mach1ML, Power BI Demonstrated performance in working on developing analytical models and deploying them in GCP. Strong drive for results, sense of urgency, and attention to detail Strong verbal and written communication skills with the ability to present to cross functional levels of management. Ability to work in a fast-paced environment with global resources under short response times and changing business needs. Familiarity with NLP, Deep Learning, neural network architectures including CNNs, RNNs, Embeddings, Transfer Learning, and Transformers. BEV experience a plus Deep understanding of Agile & PDO processes Software delivery experience a plus

Job Title :Data Science Engineer. Location :Remote (India, Ahmedabad Preferred). Shift :UK Shift. We are looking for a Data Science Engineer with 6+ years of experience in developing, deploying, and scaling machine learning models in production environments. This hybrid role combines expertise in data science and machine learning engineering to deliver impactful data-driven solutions at scale. Key Responsibilities. Design and develop machine learning models for various business problems. Implement data preprocessing, feature engineering, and model training in Python and Databricks. Work on model deployment, monitoring, and scaling in cloud or on-premise environments. Develop and optimize data pipelines to support model building and execution. Collaborate with cross-functional teams to ensure model alignment with business needs. Ensure the scalability, performance, and reliability of deployed models. Implement MLOps practices for automated testing, continuous integration, and model versioning. Monitor model performance in production and refine models as needed. Requirements. 6+ years of experience in Data Science, Machine Learning, and Model Deployment. Strong expertise in Python, Databricks, and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience with data pipeline development and cloud platforms. Knowledge of MLOps practices for scalable and automated model deployment. Strong SQL skills and experience working with large datasets. Familiarity with version control systems (e.g., Git) and containerization (e.g., Docker). Ability to work in a UK shift and collaborate with global teams. Job Type:4 years (Required). Databricks:3 years (Required). Work Location:Remote. (ref:hirist.tech). Show more Show less

Job Title :Data Science Engineer. Location :Remote (India, Ahmedabad Preferred). Shift :UK Shift. We are looking for a Data Science Engineer with 6+ years of experience in developing, deploying, and scaling machine learning models in production environments. This hybrid role combines expertise in data science and machine learning engineering to deliver impactful data-driven solutions at scale. Key Responsibilities. Design and develop machine learning models for various business problems. Implement data preprocessing, feature engineering, and model training in Python and Databricks. Work on model deployment, monitoring, and scaling in cloud or on-premise environments. Develop and optimize data pipelines to support model building and execution. Collaborate with cross-functional teams to ensure model alignment with business needs. Ensure the scalability, performance, and reliability of deployed models. Implement MLOps practices for automated testing, continuous integration, and model versioning. Monitor model performance in production and refine models as needed. Requirements. 6+ years of experience in Data Science, Machine Learning, and Model Deployment. Strong expertise in Python, Databricks, and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Experience with data pipeline development and cloud platforms. Knowledge of MLOps practices for scalable and automated model deployment. Strong SQL skills and experience working with large datasets. Familiarity with version control systems (e.g., Git) and containerization (e.g., Docker). Ability to work in a UK shift and collaborate with global teams. Job Type :Full-time. Schedule :UK shift. Application Question(s). Please provide your current CTC, expected CTC and Notice period along with the application. The applications without this information may not be considered. Education :Bachelor's (Required). Experience :Python:4 years (Required). Databricks :3 years (Required). Work Location :Remote. (ref:hirist.tech). Show more Show less

Make an impact with NTT DATA Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive. Your day at NTT DATA The Application Virtualization Engineer (L3) is a developing engineering role, responsible for providing a managed service to clients to ensure that their Cloud infrastructure remain operational through proactively monitoring, identifying, investigating, and resolving cloud-based incidents, service requests and alerts. The primary objective of this role is to proactively review client requests or tickets and apply technical/process knowledge to resolve them without breaching service level agreement (SLA) and focuses on second-line support for incidents and requests with a medium level of complexity to ensure the smooth operation and optimization of clients' cloud infrastructure and services. The Application Virtualization Engineer(L3) may also contribute to / support on project work as and when required. What you'll be doing Job Description Desired Skills : Min 8 to 12 years of experience in managing and maintaining Citrix systems (Wem,MCS,PVS,AppLayering ,Cloud PaaS) Expertise on Citrix Cloud Expertise on VMWare Horizon View , VMWare Horizon Cloud , Azure VDI,Microsoft FSlogix Certification: CCA-V / CC-VAD-CC /CCP-V Job Description : Experience in administering and supporting Citrix systems (Wem,MCS,PVS,AppLayering ,Cloud PaaS) Experience in administering VMWare Horizon View , VMWare Horizon Cloud , Azure VDI,Microsoft FSlogix Daily maintenance and troubleshooting of the servers in Citrix Administration on Citrix PVS for server maintenance (ongoing task), upgrades (ongoing task), and image maintenance/updates/upgrades (ongoing task) Make architectural and operational recommendations applying updates to the Citrix environments Maintenance/monitoring/upgrading/troubleshooting Supports applications, hardware, operating systems and network infrastructure Configuration, deployment, proactive monitoring and maintenance of EPIC-related tasks Following vendor and Epic best practices for hardware and software configuration Drawing upon concepts of tools, technologies and methodologies to collaborate with other technical specialists when carrying out assigned duties Good technical knowledge depth on MS Operating System Good experience on VMWare Horizon 8.x Good Experience on Active Directory GPO related tasks Azure Knowledge Required proven experience in managing public cloud environments, particularly with platforms such as AWS, Azure, or Google Cloud Platform. Managing and maintaining the cloud infrastructure to ensure optimal performance, availability, and scalability. Implementing and overseeing cloud security measures, including identity and access management, network configurations, and data protection. Monitoring cloud services and resources, analyzing system performance, and making recommendations for improvements. Automating cloud operations and workflows using scripting languages and automation tools like Terraform, Ansible, or AWS CloudFormation. Strong knowledge of cloud services, architectures, and deployment models. Workplace type : Hybrid Working About NTT DATA NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long-term success. We invest over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure, and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group and headquartered in Tokyo. Equal Opportunity Employer NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Join our growing global team and accelerate your career with us. Apply today.

In this role, you will: Lead complex, large-scale model maintenance, optimization, and planning initiatives related to operational processes, controls, reporting, testing, implementation, and documentation Review and analyze complex multi-faceted model operations and optimization challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors Develop model processes and optimization strategies for short- and long-term objectives; support and provide insights regarding a wide array of business initiatives Make decisions in complex and multi-faceted situations requiring solid understanding of agile development Influence global assessment of model maintenance schedules inclusive of engineering, structure, and scope of review following the System Development Life Cycle process, quality, security, and compliance requirements Strategically collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals Required Qualifications: 5+ years of quantitative model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Bachelors/masters degree in engineering field like computer science, Information technology, Electrical Engineering etc. M.Sc./M.Phil. in statistics/ economics/ mathematics/ operations research engineering physics 9 - 12 years of relevant hands-on experience in model development/monitoring/validation and Implementation. Must have hands on exposure in SAS, Python, PySpark and SQL. Expert in data mining and statistical analysis. Experience in developing, validating, monitoring models. Statistical models linear regression, logistic regression, time series analysis, multivariate statistical analysis Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned Experience in model deployment, User Acceptance Testing (UAT) and model monitoring. Critical thinking and strong problem-solving skills. Ability to learn the business aspects quickly Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable Ability to multi-task and prioritize between projects Ability to work independently and as part of a team Ability to research and report on a variety of issues using problem solving skills Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment Job Expectations: Primary role is to perform highly complex activities, advanced analytics, related to creation, validation, monitoring, implementation, documentation, articulation and defense, on-going maintenance of complex models grounded in highly statistical theory used to quantify, analyze and manage credit risks or to forecasts losses and compute capital requirements or enable decision making in business, product or other functional areas. Duties typically include implementing, validating and documenting analytical models and strategies for short and long-term objectives, performing analytical support and/or modeling, and providing well-articulated insights regarding a wide array of business initiatives. The Senior Quantitative Engineering Specialist is expected to apply predictive analytics & business knowledge in order to serve as a subject matter expert, analyst, advisor and consultant to the corporate and/or lines of business (LoB) management, such as Consumer, Commercial, Small Business Banking and Cards, with respect to modeling implementation, model validation, modeling data analytics, model performance analysis and model execution This may involve recommending advances in modeling methodologies and/or overall modeling approach/ infrastructure, high performance computing.

Immediate joiners preferred/Serving NP preferred Mandate skills- MLOPS, End - End Deployment,Data pipeline,Machine learning,Model building,Model development 6+ years exp of which 3+ years of relevant data science experience and at least 3 years of software development experience. Experience in devising creative analytical approaches to solve business problems Developing and enhancing algorithms and models to solve business problem Maintaining all models along with development and updating of code and process documentation Designing a solution approach, leading a team to deploy and maintain it in production. Proficient in Structured programming language is a must - such as Python, C/C++, Java is mandatory. Cloud concepts and significant hands-on experience with at least one cloud provider. Should be knowledgeable about the pros and cons of the various services and comfortable discussing the tradeoffs with stakeholders. Strong SQL skills. Good knowledge of Data science approaches, machine learning algorithms and statistical methods. ETL and Data Engineering pipelines using Spark/PySpark. Workflow orchestration tools like Airflow.

Project Description: Grid Dynamics wants to build a centralized, observable and secure platform for their ML, Computer Vision, LLM and SLM models. Grid Dynamics wants to onboard a vast number of AI agents, able to cover multiple required skills, ensuring a certain level of control and security in regards to their usage and availability. The observable platform must be vendor-agnostic, easy to extend to multiple type of AI applications and flexible in terms of technologies, frameworks and data types. This project is focused on establishing a centralized LLMOps capability where every ML, CV, AI-enabled application is monitored, observed, secured and provides logs of every activity. The solution consists of key building blocks such monitor every step in a RAG, Multimodal RAG or Agentic Platform, track performances and provide curated datasets for potential fine-tuning. Alignment with business scenarios, PepVigil provides also certain guardrails that allow or block interactions user-to-agent, agent-to-agent or agent-to-user. Also, Guardrails will enable predefined workflows, aimed to give more control over the series of LLM chains. Details on Tech Stack Job Qualifications and Skill Sets Advanced degree in Data Science, Computer Science, Statistics, or a related field Setting up Agent Mesh (LangSmith) Setting up Agent communication protocols (JSON/XML etc) Setting up message queues, CI/CD pipelines (Azure Queue Storage, Azure DevOps) Setting up integrations Langgrah, LangFuse Knowledge on Observability tool Arize-Phoenix tools Managing Agent Registry, Integrating with AgentAuth framework like Composio Setting up AgentCompute (Sandpack, E2BDev, Assistant APIs) Integration with IAM (Azure IAM, OKTA) Performing/Configuring Dynamic Orchestration and agent permissions Tech Stack Required: ML MLOPs Agent (Agent / Agent Mesh) LangFuse, LanChain, LangGraph Deployments (Docker, Jenkins, Kubernetes) Cloud Platforms: Azure/AWS/GCP We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office

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. Qualifications 15 years full time education

Responsibilities Design, develop, test, and maintain complex software programs, including modules, features, and components, while ensuring alignment with project specifications. Gather and evaluate software project requirements, communicate effectively with stakeholders, and troubleshoot complex software issues to recommend or implement solutions. Collaborate with management to plan, schedule, and assign projects to development teams, ensuring timely delivery and resource optimization. Participate in design and code reviews, interact with the Quality Assurance team, and contribute to test procedures to ensure system quality, performance, and reliability. Write and maintain technical documentation, provide input for user documentation, and review materials for technical accuracy and completeness Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 4-5 years of experience developing enterprise applications using Java, J2EE, and related technologies. Hands-on experience with RDBMS (e.g., Oracle, IBM DB2) and NoSQL databases (e.g., Cassandra). Strong understanding of advanced algorithms for designing and developing enterprise-grade software. Experience in writing code with streaming tools like Kafka and leveraging cloud functions (serverless compute). In-depth knowledge of microservice architecture and deployment models for enterprise-grade cloud environments. Preferred technical and professional experience Proficiency in software development tools and methods, related software languages, test design, configuration, and integration with systems, applications, products, and services. Strong written and verbal communication skills. Ability to test, analyze data, and provide actionable recommendations. Proven organizational skills, with the ability to prioritize tasks effectively and provide guidance to less experienced team members. Expertise in debugging and troubleshooting issues related to memory, performance, battery usage, and network optimization.