Overview As a Technical Architect , you will play a pivotal role in defining, designing, and overseeing the technical architecture of our projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. You will also act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities Define technical architecture and lead design discussions for scalable, secure, and high-performance applications Provide hands-on coding and technical expertise across the full technology stack Design and implement solutions using Java, Python, and Node.js ecosystems Architect event-driven systems and messaging architectures using Kafka and other messaging platforms Design and oversee data pipelines and data engineering solutions Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions Drive adoption of cloud-native, microservices, and modern architecture practices Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures Act as a mentor and technical coach for software engineers across levels Continuously evaluate and recommend new tools, frameworks, and practices Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience Around 15 years of IT industry experience , with at least 5+ years in an architect role Strong hands-on coding capability with proven expertise in: Backend: Java with Spring Boot framework (microservices, REST APIs, Spring Cloud) Python (Django/FastAPI/Flask) Node.js (Express, NestJS) Frontend: React and Angular (mandatory), with strong JavaScript/TypeScript fundamentals Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code Strong knowledge of system design, architecture patterns, and distributed systems Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) Experience with message queuing systems and event-driven architectures Ability to design for scalability, performance, and security Strong leadership, communication, and collaboration skills Experience in mentoring and developing engineering teams Exposure to Agile/Scrum methodology Highly Desired Willingness and enthusiasm to learn emerging technologies , particularly: LLM stacks (OpenAI, Claude, LangChain, Vector databases) AI/ML Engineering fundamentals RAG architectures and prompt engineering Experience with GraphQL and modern API design patterns Knowledge of data modeling and analytics platforms Familiarity with observability and monitoring tools What We're Looking For A technical leader who codes alongside the team, not just architects from the sidelines Someone passionate about continuous learning and staying ahead of technology curves A professional who can balance architectural excellence with pragmatic delivery An individual excited about the intersection of traditional engineering and AI capabilities This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions. Preference will be given to candidates from Kerala.
Role Overview: As a Senior Technology Engineer, your primary responsibility will be to drive the engineering function of the organization. You will focus on designing, developing, implementing, standardizing, and automating infrastructure products. Your role will play a crucial part in advancing the software-defined datacenter and hybrid cloud journey by utilizing SRE/DevOps, Infrastructure as Code (IaC), and Agile methodologies. Key Responsibilities: - Drive projects to eliminate non-compliant products and enforce standardized infrastructure stacks. - Automate deployments using tools such as Terraform, Ansible, Jenkins, and GitOps. - Conduct peer code reviews and enforce best practices in Infrastructure as Code (IaC). - Define and execute product strategy, roadmap, and backlog in 2-week sprints. - Lead cloud migration initiatives to public cloud platforms such as Azure, AWS, and OCI. - Optimize infrastructure for performance, cost, and security. - Reduce Total Cost of Ownership (TCO) through automation, open-source adoption, and vendor engagement. - Implement zero-touch deployments and self-healing infrastructure. - Address audit, risk, and compliance items proactively. - Research and integrate emerging technologies like Kubernetes, OpenShift, and ELK stack. - Troubleshoot complex issues across networking (SD-WAN, DNS, load balancers), security (SSL, CyberArk, HashiCorp Vault), and databases (Oracle, MSSQL, MongoDB). - Enhance CI/CD pipelines for infrastructure and database automation. Qualifications Required: - Bachelors in Computer Science or equivalent is essential. - Red Hat Certified Architect (RHCA), Azure/AWS/OCI Cloud Architect certification is essential. - 8+ years of experience in infrastructure engineering, leading cloud migration projects to Azure/AWS/OCI. - Expertise in Terraform, Ansible, Jenkins, GitOps. - Hands-on experience with Linux, Windows, scripting (Bash/Python/Groovy), and containerization (Docker/Kubernetes/OpenShift). - Strong knowledge of networking (SD-WAN, DNS, firewalls), security (SSL/TLS, certificates, CyberArk), and databases. Location: Onsite at Chennai, Bengaluru.,
Overview As a Technical Architect , you will play a pivotal role in defining, designing, and overseeing the technical architecture of our projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. You will also act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities Define technical architecture and lead design discussions for scalable, secure, and high-performance applications Provide hands-on coding and technical expertise across the full technology stack Design and implement solutions using Java, Python, and Node.js ecosystems Architect event-driven systems and messaging architectures using Kafka and other messaging platforms Design and oversee data pipelines and data engineering solutions Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions Drive adoption of cloud-native, microservices, and modern architecture practices Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures Act as a mentor and technical coach for software engineers across levels Continuously evaluate and recommend new tools, frameworks, and practices Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience Around 15 years of IT industry experience , with at least 5+ years in an architect role Strong hands-on coding capability with proven expertise in: Backend: Java with Spring Boot framework (microservices, REST APIs, Spring Cloud) Python (Django/FastAPI/Flask) Node.js (Express, NestJS) Frontend: React and Angular (mandatory), with strong JavaScript/TypeScript fundamentals Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code Strong knowledge of system design, architecture patterns, and distributed systems Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) Experience with message queuing systems and event-driven architectures Ability to design for scalability, performance, and security Strong leadership, communication, and collaboration skills Experience in mentoring and developing engineering teams Exposure to Agile/Scrum methodology Highly Desired Willingness and enthusiasm to learn emerging technologies , particularly: LLM stacks (OpenAI, Claude, LangChain, Vector databases) AI/ML Engineering fundamentals RAG architectures and prompt engineering Experience with GraphQL and modern API design patterns Knowledge of data modeling and analytics platforms Familiarity with observability and monitoring tools What We're Looking For A technical leader who codes alongside the team, not just architects from the sidelines Someone passionate about continuous learning and staying ahead of technology curves A professional who can balance architectural excellence with pragmatic delivery An individual excited about the intersection of traditional engineering and AI capabilities This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions. Preference will be given to candidates from Kerala.
We are seeking a highly skilled Microsoft SQL Server Developer with extensive hands-on experience in designing, developing, and optimizing SQL Server databases. The ideal candidate will have deep expertise in writing complex SQL queries, stored procedures, triggers, user-defined functions, and performance tuning. In addition, the developer should be familiar with modern SQL Server features including event-based triggers, file arrival monitoring, and scheduling jobs. Key Responsibilities • Design, develop, and maintain SQL Server databases, schemas, tables, views, stored procedures, triggers, and user-defined functions. • Write optimized SQL queries for high-performance applications and large data sets. • Develop triggers and automation workflows (e.g., event-driven triggers when files arrive, scheduled jobs using SQL Server Agent). • Implement ETL logic and integrate external data sources into SQL Server. • Optimize database performance through indexing, query tuning, and execution plan analysis. • Ensure database reliability, security, and compliance with best practices. • Collaborate with application developers, data analysts, and business stakeholders to gather requirements and deliver database solutions. • Troubleshoot production issues related to database queries, procedures, and processes. • Stay updated with the latest SQL Server features (Always On, In-Memory OLTP, partitioning, temporal tables, etc.) and recommend adoption where applicable. Required Skills & Qualifications • Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. • 5+ years of proven experience as a SQL Server Developer . • Strong expertise in T-SQL , stored procedures, triggers, functions, and views. • Hands-on experience with SQL Server Agent for job scheduling, alerts, and monitoring. • Experience with event-driven triggers (e.g., file arrival, CDC, Service Broker, or related technologies). • Excellent knowledge of performance tuning and query optimization. • Proficiency in data modeling and database design principles. • Familiarity with ETL processes and integration with external systems. • Strong debugging and problem-solving skills. • Knowledge of source control tools (e.g., Git, Azure DevOps) for managing database code. Nice-to-Have Skills • Python scripting • Docker • Camunda
As a Sr. Technology Engineer - Compute, you will lead the engineering function by focusing on designing, developing, automating, and standardizing infrastructure products. Your expertise in Linux, virtualization, automation, and cloud technologies will be crucial for this role, with an emphasis on IaC, GitOps, and open-source innovation. - Design, implement, and automate infrastructure solutions using Terraform, Ansible, and Jenkins. - Standardize the compute stack across data centers for compliance with security and operational policies. - Optimize Total Cost of Ownership (TCO) through automation, vendor engagement, and open-source adoption. - Enhance operational stability by proactively addressing risks, audit findings, and problem tickets. - Collaborate with architects, security, and risk teams to align solutions with enterprise standards. - Lead troubleshooting efforts, conduct root cause analysis, and implement preventive measures. - Provide support for on-call escalations as needed. Qualifications Required: - Bachelor's degree in Computer Science or equivalent. - Red Hat Certified Architect or equivalent certification. - Minimum 10 years of experience in infrastructure engineering in large-scale environments. - Strong expertise in automation tools such as Ansible, Terraform, Jenkins, and GitOps. - Deep knowledge of Linux (RHEL/Ubuntu) and Windows internals. - Experience with virtualization technologies like KVM, oVirt, and OpenStack. - Background in banking/financial services is preferred.,
As a Technical Architect, you will play a pivotal role in defining, designing, and overseeing the technical architecture of projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. Additionally, you will act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities: - Define technical architecture and lead design discussions for scalable, secure, and high-performance applications - Provide hands-on coding and technical expertise across the full technology stack - Design and implement solutions using Java, Python, and Node.js ecosystems - Architect event-driven systems and messaging architectures using Kafka and other messaging platforms - Design and oversee data pipelines and data engineering solutions - Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions - Drive adoption of cloud-native, microservices, and modern architecture practices - Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems - Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards - Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures - Act as a mentor and technical coach for software engineers across levels - Continuously evaluate and recommend new tools, frameworks, and practices - Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience: - Around 15 years of IT industry experience, with at least 5+ years in an architect role - Strong hands-on coding capability with proven expertise in: - Backend: Java with Spring Boot framework, Python (Django/FastAPI/Flask), Node.js (Express, NestJS) - Frontend: React and Angular, with strong JavaScript/TypeScript fundamentals - Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) - DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code - Strong knowledge of system design, architecture patterns, and distributed systems - Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) - Experience with message queuing systems and event-driven architectures - Ability to design for scalability, performance, and security - Strong leadership, communication, and collaboration skills - Experience in mentoring and developing engineering teams - Exposure to Agile/Scrum methodology Highly Desired: - Willingness and enthusiasm to learn emerging technologies, particularly: LLM stacks, AI/ML Engineering fundamentals, RAG architectures, and prompt engineering - Experience with GraphQL and modern API design patterns - Knowledge of data modeling and analytics platforms - Familiarity with observability and monitoring tools This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions.,
Overview As a Technical Architect , you will play a pivotal role in defining, designing, and overseeing the technical architecture of our projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. You will also act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities Define technical architecture and lead design discussions for scalable, secure, and high-performance applications Provide hands-on coding and technical expertise across the full technology stack Design and implement solutions using Java, Python, and Node.js ecosystems Architect event-driven systems and messaging architectures using Kafka and other messaging platforms Design and oversee data pipelines and data engineering solutions Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions Drive adoption of cloud-native, microservices, and modern architecture practices Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures Act as a mentor and technical coach for software engineers across levels Continuously evaluate and recommend new tools, frameworks, and practices Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience Around 15 years of IT industry experience, with at least 5+ years in an architect role Strong hands-on coding capability with proven expertise in: Backend: Java with Spring Boot framework (microservices, REST APIs, Spring Cloud) Python (Django/FastAPI/Flask) Node.js (Express, NestJS) Frontend: React and Angular (mandatory), with strong JavaScript/TypeScript fundamentals Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code Strong knowledge of system design, architecture patterns, and distributed systems Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) Experience with message queuing systems and event-driven architectures Ability to design for scalability, performance, and security Strong leadership, communication, and collaboration skills Experience in mentoring and developing engineering teams Exposure to Agile/Scrum methodology Highly Desired Willingness and enthusiasm to learn emerging technologies, particularly: LLM stacks (OpenAI, Claude, LangChain, Vector databases) AI/ML Engineering fundamentals RAG architectures and prompt engineering Experience with GraphQL and modern API design patterns Knowledge of data modeling and analytics platforms Familiarity with observability and monitoring tools What We're Looking For A technical leader who codes alongside the team, not just architects from the sidelines Someone passionate about continuous learning and staying ahead of technology curves A professional who can balance architectural excellence with pragmatic delivery An individual excited about the intersection of traditional engineering and AI capabilities This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions. Preference will be given to candidates from Kerala.
We are seeking an AI/ML Engineer with over 5 years of expertise in conventional machine learning and experience or interest in generative AI to develop Sports Companion GPT - Aiko for sports applications, specifically targeting Cricket and Football. The ideal candidate will have extensive experience building and optimizing ML models and working with large datasets, with experience in fine-tuning generative AI models and familiarity with Azure cloud platforms as a plus. Previous experience with sports-related datasets is advantageous but not mandatory. Based in Delhi, you will collaborate with data scientists, software engineers, and sports domain experts across our global teams to create an AI model that delivers actionable insights and innovative solutions, while also contributing to the development of a generative AI evaluation framework. Key Responsibilities: • Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics. • Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports, if applicable. • Gen AI Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications. • Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models. • Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases. • Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications. • Collaboration: Work with sports analysts, data engineers, and domain experts across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives. • Deployment & Optimization: Deploy models into production environments, preferably leveraging Azure cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications. • Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks. • Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing. • Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs. Qualifications: Experience: • 5+ years in AI/ML engineering, with significant experience in conventional ML. • Proven expertise in building ML models (e.g., Scikit-learn, XGBoost). • Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory. • Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory. • Technical Skills: • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs). • Experience with data preprocessing, feature engineering, and handling large datasets. • Familiarity with cloud platforms for model training and deployment, with Azure experience as a strong plus. • Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines. • Experience with computer vision, natural language processing, or text generation is a plus. • Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required. • Soft Skills: • Strong problem-solving and analytical skills. • Effective communication and collaboration skills for cross-functional and global teamwork. • Ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: • Experience fine-tuning large language models or generative AI for domain-specific applications. • Experience developing evaluation frameworks for generative AI models. • Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment. • Experience with real-time or streaming data for sports applications. • Knowledge of reinforcement learning or multimodal AI models. • Familiarity with sports technologies, such as player tracking systems or wearables. • Contributions to open-source AI/ML projects or published research in relevant fields.
Role Overview We are seeking a highly experienced Senior Business Analyst to lead requirement analysis, stakeholder communication, and solution design across multiple projects. The ideal candidate will have a proven ability to bridge the gap between business needs and technical solutions, working closely with clients, product teams, and developers to deliver impactful results. This is a hybrid role offering flexibility, collaboration, and opportunities to work on global projects. Key Responsibilities Lead and manage the end-to-end business analysis process across complex software projects. Conduct detailed requirement gathering sessions with clients and stakeholders. Translate business needs into detailed functional and technical specifications, use cases, and process flows. Collaborate closely with UI/UX designers, developers, and QA teams to ensure requirements are fully understood and implemented. Analyze existing systems and propose process improvements or automation opportunities. Develop business cases, feasibility studies, and ROI analysis for proposed solutions. Facilitate workshops, sprint planning sessions, and client demos. Ensure traceability of requirements throughout the project lifecycle. Identify project risks, dependencies, and impacts early and provide mitigation strategies. Mentor junior analysts and contribute to best practices in documentation and process improvement. Required Skills & Experience Bachelor’s or Master’s degree in Computer Science, Information Technology, Business Administration, or related field. 10+ years of experience as a Business Analyst, preferably in custom software or enterprise application development. Strong understanding of SDLC, Agile methodologies (Scrum/Kanban), and product lifecycle management. Expertise in preparing BRDs, FRDs, user stories, wireframes, and process diagrams. Proficiency with tools such as Jira, Confluence, Figma, Lucidchart, or MS Visio. Excellent analytical, problem-solving, and critical thinking skills. Strong communication and presentation abilities to engage with C-level stakeholders and technical teams alike. Experience in domains such as education, fintech, ERP, or SaaS products is a plus. What We Offer Hybrid working model – flexibility to balance office and remote work. Opportunity to work on global projects with diverse teams. Learning-driven culture with access to training and upskilling programs. Collaborative and innovative work environment.
Overview As a Technical Architect , you will play a pivotal role in defining, designing, and overseeing the technical architecture of our projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. You will also act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities Define technical architecture and lead design discussions for scalable, secure, and high-performance applications Provide hands-on coding and technical expertise across the full technology stack Design and implement solutions using Java, Python, and Node.js ecosystems Architect event-driven systems and messaging architectures using Kafka and other messaging platforms Design and oversee data pipelines and data engineering solutions Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions Drive adoption of cloud-native, microservices, and modern architecture practices Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures Act as a mentor and technical coach for software engineers across levels Continuously evaluate and recommend new tools, frameworks, and practices Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience Around 15 years of IT industry experience , with at least 5+ years in an architect role Strong hands-on coding capability with proven expertise in: Backend: Java with Spring Boot framework (microservices, REST APIs, Spring Cloud) Python (Django/FastAPI/Flask) Node.js (Express, NestJS) Frontend: React and Angular (mandatory), with strong JavaScript/TypeScript fundamentals Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code Strong knowledge of system design, architecture patterns, and distributed systems Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) Experience with message queuing systems and event-driven architectures Ability to design for scalability, performance, and security Strong leadership, communication, and collaboration skills Experience in mentoring and developing engineering teams Exposure to Agile/Scrum methodology Highly Desired Willingness and enthusiasm to learn emerging technologies , particularly: LLM stacks (OpenAI, Claude, LangChain, Vector databases) AI/ML Engineering fundamentals RAG architectures and prompt engineering Experience with GraphQL and modern API design patterns Knowledge of data modeling and analytics platforms Familiarity with observability and monitoring tools What We're Looking For A technical leader who codes alongside the team, not just architects from the sidelines Someone passionate about continuous learning and staying ahead of technology curves A professional who can balance architectural excellence with pragmatic delivery An individual excited about the intersection of traditional engineering and AI capabilities This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions. Preference will be given to candidates from Kerala.
We are seeking an AI/ML Engineer with over 5 years of expertise in conventional machine learning and experience or interest in generative AI to develop Sports Companion GPT - Aiko for sports applications, specifically targeting Cricket and Football. The ideal candidate will have extensive experience building and optimizing ML models and working with large datasets, with experience in fine-tuning generative AI models and familiarity with Azure cloud platforms as a plus. Previous experience with sports-related datasets is advantageous but not mandatory. Based in Delhi, you will collaborate with data scientists, software engineers, and sports domain experts across our global teams to create an AI model that delivers actionable insights and innovative solutions, while also contributing to the development of a generative AI evaluation framework. Key Responsibilities: • Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics. • Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports, if applicable. • Gen AI Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications. • Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models. • Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases. • Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications. • Collaboration: Work with sports analysts, data engineers, and domain experts across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives. • Deployment & Optimization: Deploy models into production environments, preferably leveraging Azure cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications. • Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks. • Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing. • Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs. Qualifications: Experience: • 5+ years in AI/ML engineering, with significant experience in conventional ML. • Proven expertise in building ML models (e.g., Scikit-learn, XGBoost). • Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory. • Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory. • Technical Skills: • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs). • Experience with data preprocessing, feature engineering, and handling large datasets. • Familiarity with cloud platforms for model training and deployment, with Azure experience as a strong plus. • Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines. • Experience with computer vision, natural language processing, or text generation is a plus. • Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required. • Soft Skills: • Strong problem-solving and analytical skills. • Effective communication and collaboration skills for cross-functional and global teamwork. • Ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: • Experience fine-tuning large language models or generative AI for domain-specific applications. • Experience developing evaluation frameworks for generative AI models. • Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment. • Experience with real-time or streaming data for sports applications. • Knowledge of reinforcement learning or multimodal AI models. • Familiarity with sports technologies, such as player tracking systems or wearables. • Contributions to open-source AI/ML projects or published research in relevant fields.
About the Role We are looking for an experienced Full Stack Developer with strong expertise in React for front-end development and solid hands-on experience with Python for back-end services. The ideal candidate will be responsible for designing, developing, and maintaining scalable, high-performance web applications. You will collaborate closely with cross-functional teams, contribute to architectural decisions, and ensure top-quality code delivery. Key Responsibilities Develop and maintain responsive, high-quality front-end interfaces using React, TypeScript, and modern UI frameworks. Build and enhance backend services, APIs, and business logic using Python (Django/FastAPI/Flask). Collaborate with product managers, designers, and other engineers to translate requirements into scalable technical solutions. Optimize application performance, ensure cross-browser compatibility, and maintain code quality through reviews and best practices. Integrate third-party services, APIs, and internal systems. Troubleshoot, debug, and resolve technical issues across the stack. Participate in architecture discussions and contribute to improving engineering processes and standards. Work with databases (SQL/NoSQL), authentication systems, and CI/CD pipelines. Required Skills & Qualifications 5+ years of professional experience in full stack development. Strong expertise in React , modern JavaScript, TypeScript, Redux or other state management tools. Solid backend development experience using Python with frameworks such as Django, FastAPI, or Flask. Experience building and consuming RESTful APIs or GraphQL services. Good understanding of database systems like Microsoft SQL Familiarity with cloud platforms (AWS/Azure) and containerization (Docker). Strong understanding of Git, CI/CD workflows, and Agile methodologies. Excellent problem-solving skills, communication, and team collaboration abilities. Good to Have Experience with microservices architecture. Knowledge of performance optimization and application security best practices. Exposure to DevOps practices and infrastructure automation tools.
About the Role We are seeking an experienced AI/ML Engineer with a strong background in designing, developing, and deploying machine learning models and AI-driven solutions. The ideal candidate will have hands-on expertise across the full ML lifecycle—from data exploration and feature engineering to model training, optimization, and production deployment. You will work closely with cross-functional teams to deliver scalable, high-impact AI solutions. Key Responsibilities Design, develop, and deploy machine learning models and end-to-end ML pipelines. Work with large structured and unstructured datasets to perform data preprocessing, feature engineering, and exploratory analysis. Build, fine-tune, and evaluate supervised, unsupervised, and deep learning models for various use cases. Develop and implement scalable inference systems, APIs, and microservices for production. Collaborate with Data Engineering, Product, and Software teams to integrate models into products and platforms. Research and implement state-of-the-art techniques in NLP, computer vision, and generative AI where applicable. Monitor model performance, automate retraining workflows, and ensure model reliability and accuracy. Optimize models for performance, scalability, and low-latency inference. Create clear technical documentation, model cards, and deployment guidelines. Mentor junior engineers and support code reviews and architecture discussions. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 5+ years of hands-on experience in machine learning, deep learning, or AI engineering. Strong proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn . Solid experience with data pipelines , ETL , and working knowledge of SQL/NoSQL databases. Experience building and deploying models using AWS / Azure / GCP services. Strong understanding of ML Ops , CI/CD, containerization (Docker), and orchestration (Kubernetes). Expertise in at least one key area such as NLP, Computer Vision, Time-Series Forecasting, or Generative AI . Working knowledge of version control (Git), model versioning, and experiment tracking tools such as MLflow, DVC , or similar. Ability to write clean, optimized, and production-quality code. Strong problem-solving abilities, analytical skills, and a deep understanding of ML algorithms. Preferred Skills Experience with LLMs , prompt engineering, vector databases, or retrieval-augmented systems (RAG). Familiarity with big data technologies (Spark, Hadoop). Experience with Bayesian optimization, AutoML frameworks, or hyperparameter tuning tools. Exposure to microservice-based architectures.
We are building the next generation of AI-powered applications that deliver actionable financial and marketing insights to our clients. As an AI Engineer focused on backend development, you'll be instrumental in designing and developing multiple agentic AI applications that integrate with data lakehouses and business intelligence platforms. This is not a single-project role. You'll work on a pipeline of AI-driven solutions across various use cases, all built on a common architecture leveraging cutting-edge LLM technologies, agentic frameworks, and cloud infrastructure. What You'll Build Agentic chatbot applications Agentic chatbot applications with conversational UI for financial and marketing insights RAG-based systems RAG-based systems that intelligently retrieve and synthesize information from enterprise data sources MCP (Model Context Protocol) integrations MCP (Model Context Protocol) integrations for tool calling and external system interactions Real-time visualization generation Real-time visualization generation including graphs, charts, and dynamic dashboards Sandboxed code execution environments Sandboxed code execution environments for safe AI-generated code runs LLM benchmarking systems LLM benchmarking systems to evaluate and switch between models (AWS Bedrock, Azure AI Foundry) as new versions emerge Data integration pipelines Data integration pipelines connecting to SQL-based data lakehouses and Tableau dashboards Key Responsibilities Development Design and develop Python backend services using FastAPI FastAPI for AI-powered applications Implement agentic workflows using LangChain LangChain and/or Azure AI agentic frameworks like AutoGen Azure AI agentic frameworks like AutoGen Build and maintain RAG systems for context-aware AI responses Develop MCP servers and integrations for tool calling and external API interactions Create sandboxed execution environments for AI-generated code and visualizations Data & SQL Write efficient SQL queries against data lakehouses to retrieve business insights Integrate with Tableau dashboards and other BI platforms Optimize data retrieval patterns for LLM context windows AI/ML Operations Build benchmarking systems to evaluate LLM performance across different models and providers Implement model switching logic to automatically use the most efficient/effective LLM Monitor and optimize token usage, costs, and response latency Work with AWS Bedrock and Azure AI Foundry for model deployment DevOps & Deployment Containerize applications using Docker Deploy and manage services in Kubernetes (K8s) clusters Build and maintain GitLab CI/CD pipelines for automated testing and deployment Ensure scalability, reliability, and security of production systems Collaboration Work directly with US-based clients to understand requirements and deliver solutions Collaborate with frontend developers (React), data engineers, and architects Participate in technical design discussions and architectural decisions Document code, APIs, and system architecture clearly Required Qualifications Technical Skills 3+ years of professional Python development experience Strong SQL skills with experience querying databases or data lakehouses Experience with FastAPI or similar Python web frameworks (Flask, Django) Hands-on experience with AWS Bedrock or Azure AI services Familiarity with Docker containerization Experience with Kubernetes (K8s) deployments Proficiency with Git and GitLab CI/CD or similar CI/CD tools Understanding of RESTful API design and development AI/ML Experience Working knowledge of LLM technologies (GPT, Claude, Llama, etc.) Experience with prompt engineering and LLM application development Familiarity with LangChain, AutoGen, Azure AI frameworks, or similar agentic/orchestration frameworks Understanding of RAG (Retrieval-Augmented Generation) patterns Soft Skills Excellent English communication skills (written and verbal) for US client interaction Ability to work autonomously and complete tasks with minimal supervision Strong problem-solving skills and attention to detail Self-motivated with ability to manage priorities and deadlines Preferred Qualifications Experience with React or frontend development (bonus, not required) Familiarity with Tableau or other BI platforms Experience with data lakehouses (Databricks, Snowflake, etc.) Knowledge of Model Context Protocol (MCP) or similar tool-calling frameworks Experience building benchmarking or evaluation systems for ML models Background in financial services or marketing analytics Contributions to open-source AI/ML projects
We are seeking an AI/ML Engineer with over 5 years of expertise in conventional machine learning and experience or interest in generative AI to develop Sports Companion GPT - Aiko for sports applications, specifically targeting Cricket and Football. The ideal candidate will have extensive experience building and optimizing ML models and working with large datasets, with experience in fine-tuning generative AI models and familiarity with Azure cloud platforms as a plus. Previous experience with sports-related datasets is advantageous but not mandatory. Based in Delhi, you will collaborate with data scientists, software engineers, and sports domain experts across our global teams to create an AI model that delivers actionable insights and innovative solutions, while also contributing to the development of a generative AI evaluation framework. Key Responsibilities: • Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics. • Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports, if applicable. • Gen AI Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications. • Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models. • Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases. • Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications. • Collaboration: Work with sports analysts, data engineers, and domain experts across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives. • Deployment & Optimization: Deploy models into production environments, preferably leveraging Azure cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications. • Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks. • Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing. • Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs. Qualifications: Experience: • 5+ years in AI/ML engineering, with significant experience in conventional ML. • Proven expertise in building ML models (e.g., Scikit-learn, XGBoost). • Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory. • Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory. • Technical Skills: • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs). • Experience with data preprocessing, feature engineering, and handling large datasets. • Familiarity with cloud platforms for model training and deployment, with Azure experience as a strong plus. • Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines. • Experience with computer vision, natural language processing, or text generation is a plus. • Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required. • Soft Skills: • Strong problem-solving and analytical skills. • Effective communication and collaboration skills for cross-functional and global teamwork. • Ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: • Experience fine-tuning large language models or generative AI for domain-specific applications. • Experience developing evaluation frameworks for generative AI models. • Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment. • Experience with real-time or streaming data for sports applications. • Knowledge of reinforcement learning or multimodal AI models. • Familiarity with sports technologies, such as player tracking systems or wearables. • Contributions to open-source AI/ML projects or published research in relevant fields.
Overview As a Technical Architect , you will play a pivotal role in defining, designing, and overseeing the technical architecture of our projects while maintaining strong hands-on coding capabilities. You will work across Frontend, Backend, DevOps, and Data Engineering domains, ensuring best practices, scalability, and efficiency in all solutions. You will also act as a mentor, guiding engineers at different levels while staying current with emerging technologies including AI/ML and LLM stacks. Key Responsibilities Define technical architecture and lead design discussions for scalable, secure, and high-performance applications Provide hands-on coding and technical expertise across the full technology stack Design and implement solutions using Java, Python, and Node.js ecosystems Architect event-driven systems and messaging architectures using Kafka and other messaging platforms Design and oversee data pipelines and data engineering solutions Collaborate with stakeholders, product managers, and development teams to translate business needs into technical solutions Drive adoption of cloud-native, microservices, and modern architecture practices Implement and oversee CI/CD pipelines, infrastructure automation, and monitoring systems Perform code reviews, design reviews, and technical audits to ensure quality and adherence to standards Explore and integrate AI/ML capabilities and LLM-based solutions into existing architectures Act as a mentor and technical coach for software engineers across levels Continuously evaluate and recommend new tools, frameworks, and practices Own technical risk management and ensure alignment with project timelines and goals Required Skills & Experience Around 15 years of IT industry experience, with at least 5+ years in an architect role Strong hands-on coding capability with proven expertise in: Backend: Java with Spring Boot framework (microservices, REST APIs, Spring Cloud) Python (Django/FastAPI/Flask) Node.js (Express, NestJS) Frontend: React and Angular (mandatory), with strong JavaScript/TypeScript fundamentals Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark) DevOps & Cloud: AWS/Azure/GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code Strong knowledge of system design, architecture patterns, and distributed systems Hands-on experience with databases (PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch) Experience with message queuing systems and event-driven architectures Ability to design for scalability, performance, and security Strong leadership, communication, and collaboration skills Experience in mentoring and developing engineering teams Exposure to Agile/Scrum methodology Highly Desired Willingness and enthusiasm to learn emerging technologies, particularly: LLM stacks (OpenAI, Claude, LangChain, Vector databases) AI/ML Engineering fundamentals RAG architectures and prompt engineering Experience with GraphQL and modern API design patterns Knowledge of data modeling and analytics platforms Familiarity with observability and monitoring tools What We're Looking For A technical leader who codes alongside the team, not just architects from the sidelines Someone passionate about continuous learning and staying ahead of technology curves A professional who can balance architectural excellence with pragmatic delivery An individual excited about the intersection of traditional engineering and AI capabilities This role offers the opportunity to shape technical direction while working with cutting-edge technologies and building next-generation solutions. Preference will be given to candidates from Kerala.
We are seeking an AI/ML Engineer with over 5 years of expertise in conventional machine learning and experience or interest in generative AI to develop Sports Companion GPT - Aiko for sports applications, specifically targeting Cricket and Football. The ideal candidate will have extensive experience building and optimizing ML models and working with large datasets, with experience in fine-tuning generative AI models and familiarity with Azure cloud platforms as a plus. Previous experience with sports-related datasets is advantageous but not mandatory. Based in Delhi, you will collaborate with data scientists, software engineers, and sports domain experts across our global teams to create an AI model that delivers actionable insights and innovative solutions, while also contributing to the development of a generative AI evaluation framework. Key Responsibilities: • Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics. • Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports, if applicable. • Gen AI Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications. • Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models. • Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases. • Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications. • Collaboration: Work with sports analysts, data engineers, and domain experts across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives. • Deployment & Optimization: Deploy models into production environments, preferably leveraging Azure cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications. • Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks. • Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing. • Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs. Qualifications: Experience: • 5+ years in AI/ML engineering, with significant experience in conventional ML. • Proven expertise in building ML models (e.g., Scikit-learn, XGBoost). • Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory. • Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory. • Technical Skills: • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs). • Experience with data preprocessing, feature engineering, and handling large datasets. • Familiarity with cloud platforms for model training and deployment, with Azure experience as a strong plus. • Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines. • Experience with computer vision, natural language processing, or text generation is a plus. • Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required. • Soft Skills: • Strong problem-solving and analytical skills. • Effective communication and collaboration skills for cross-functional and global teamwork. • Ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: • Experience fine-tuning large language models or generative AI for domain-specific applications. • Experience developing evaluation frameworks for generative AI models. • Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment. • Experience with real-time or streaming data for sports applications. • Knowledge of reinforcement learning or multimodal AI models. • Familiarity with sports technologies, such as player tracking systems or wearables. • Contributions to open-source AI/ML projects or published research in relevant fields.
We are seeking an AI/ML Engineer with over 5 years of expertise in conventional machine learning and experience or interest in generative AI to develop Sports Companion GPT - Aiko for sports applications, specifically targeting Cricket and Football. The ideal candidate will have extensive experience building and optimizing ML models and working with large datasets, with experience in fine-tuning generative AI models and familiarity with Azure cloud platforms as a plus. Previous experience with sports-related datasets is advantageous but not mandatory. Based in Delhi, you will collaborate with data scientists, software engineers, and sports domain experts across our global teams to create an AI model that delivers actionable insights and innovative solutions, while also contributing to the development of a generative AI evaluation framework. Key Responsibilities: • Model Development: Design and develop AI models for Sports Companion GPT - Aiko, combining conventional ML techniques (e.g., regression, classification, clustering) with generative AI models for Cricket and Football applications, such as player performance prediction, game strategy optimization, injury risk assessment, or fan engagement analytics. • Generative AI Fine-Tuning: Fine-tune pre-trained generative AI models (e.g., transformers, GANs) using Cricket and Football-specific datasets to generate insights, predictions, or content tailored to these sports, if applicable. • Gen AI Evaluation Framework: Develop and implement a robust evaluation framework for generative AI models, including metrics for accuracy, relevance, coherence, and domain-specific performance in sports applications. • Data Processing: Process and analyze large, complex datasets (e.g., player statistics, video analysis, sensor data, or text data) to prepare data for training both ML and generative AI models. • Algorithm Development: Implement and optimize ML algorithms and generative AI architectures, ensuring seamless integration for Cricket and Football use cases. • Model Training & Evaluation: Train, fine-tune, and evaluate models to achieve high accuracy, scalability, and robustness, using metrics relevant to sports applications. • Collaboration: Work with sports analysts, data engineers, and domain experts across India, the UK, Singapore, and the Middle East to incorporate domain knowledge into Aiko and align with business objectives. • Deployment & Optimization: Deploy models into production environments, preferably leveraging Azure cloud platforms, ensuring efficient inference for real-time or near-real-time sports applications. • Research: Stay updated on advancements in ML and generative AI, applying relevant techniques to improve model performance and evaluation frameworks. • Documentation: Document model architectures, fine-tuning processes, evaluation frameworks, and performance metrics for reproducibility and knowledge sharing. • Ethical AI: Ensure models are developed with fairness, transparency, and ethical considerations, mitigating biases in predictions or generated outputs. Qualifications: Experience: • 5+ years in AI/ML engineering, with significant experience in conventional ML. • Proven expertise in building ML models (e.g., Scikit-learn, XGBoost). • Experience with fine-tuning generative AI models (e.g., Hugging Face, TensorFlow, PyTorch) is a plus but not mandatory. • Previous experience with sports-related datasets, particularly Cricket or Football, is a plus but not mandatory. • Technical Skills: • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Strong knowledge of conventional ML algorithms (e.g., regression, decision trees, SVMs) and familiarity with generative AI architectures (e.g., transformers, GANs). • Experience with data preprocessing, feature engineering, and handling large datasets. • Familiarity with cloud platforms for model training and deployment, with Azure experience as a strong plus. • Knowledge of MLOps practices, including model versioning, monitoring, and CI/CD pipelines. • Experience with computer vision, natural language processing, or text generation is a plus. • Domain Knowledge: Familiarity with Cricket or Football analytics, biomechanics, or performance metrics is an advantage but not required. • Soft Skills: • Strong problem-solving and analytical skills. • Effective communication and collaboration skills for cross-functional and global teamwork. • Ability to explain technical concepts to non-technical stakeholders. Preferred Qualifications: • Experience fine-tuning large language models or generative AI for domain-specific applications. • Experience developing evaluation frameworks for generative AI models. • Familiarity with Azure cloud services (e.g., Azure Machine Learning, Azure Kubernetes Service, or Azure Data Lake) for model development and deployment. • Experience with real-time or streaming data for sports applications. • Knowledge of reinforcement learning or multimodal AI models. • Familiarity with sports technologies, such as player tracking systems or wearables. • Contributions to open-source AI/ML projects or published research in relevant fields.