Job Summary We are looking for a skilled and passionate Mobile Application Developer with expertise in React Native to join our dynamic and collaborative team. You will play a key role in designing, developing, and maintaining high-performance mobile and web applications. This role requires a strong foundation in computer science principles, a keen eye for UI/UX, and the ability to thrive in an agile development environment. Key Responsibilities Collaborate with senior engineers, designers, and product managers to build intuitive and high-quality user interfaces. Develop and maintain mobile applications using React Native , and contribute to web applications built with React.js and Next.js . Write clean, maintainable code with a focus on performance and scalability. Build reusable components and libraries for future use. Translate UI/UX designs into functional, responsive interfaces. Optimize applications for maximum speed and responsiveness. Perform unit and integration testing using tools like Jest and Enzyme (Snapshot testing included). Participate in code reviews and contribute to a high-standard engineering culture using tools like ESLint , Prettier , and Snippets . Work in an Agile environment, using JIRA for task management and Bitbucket for source control. Ensure application stability and performance through debugging and troubleshooting. Stay current with emerging technologies and industry trends. Required Qualifications Strong proficiency in React Native , React.js , Next.js , GraphQL , HTML , and CSS . Solid experience with Node.js and PostgreSQL . Deep understanding of object-oriented programming and software architecture principles. Experience with testing frameworks such as Jest and Enzyme . Familiarity with development tools including ESLint , Prettier , and code snippets . Hands-on experience working in Agile/Scrum teams. Excellent problem-solving, debugging, and technical design skills. Strong foundation in computer science fundamentals including data structures , algorithms , and OO design . Effective communication and team collaboration skills. Preferred Qualifications (Nice to Have) Experience with mobile app deployment to App Store and Google Play . Familiarity with CI/CD pipelines for mobile and web apps. Understanding of performance monitoring and analytics tools.

We are seeking a highly skilled AI Engineer with demonstrated expertise in both traditional Machine Learning modelling and modern GenAI techniques. This role involves building scalable AI systems using foundation models, parameter- efficient fine-tuning (PEFT), and robust MLOps pipelines, while also grounding your solutions in classical machine learning principles. The ideal candidate excels at blending structured data modelling with large language model capabilities to drive intelligent, efficient, and production-ready AI systems. Key Responsibilities: Design, build, and deploy predictive systems by combining traditional ML models (e.g., regression, tree-based, time series) with Generative AI capabilities (e.g., LLMs, embeddings, GenAI-based simulation). Strong skills in prompt engineering are required to support the development and deployment of generative AI solutions. Fine-tune foundation models using PEFT techniques (e.g., LoRA, prefix tuning, adapters) for domain-specific applications. Build and maintain end-to-end MLOps pipelines for model versioning, testing, deployment, monitoring, and retraining. Use LLMs for automating feature generation, synthetic data creation, and prompt-driven scenario modelling. Manage the full AI/ML model lifecycle: experimentation, deployment, monitoring, diagnostics, and iterative enhancements. Apply and validate classical ML algorithms (e.g., XGBoost, LightGBM, ARIMA, SVMs, etc.) as benchmarks or hybrid components. Collaborate with cross-functional teams (data scientists, ML engineers, DevOps, product) to deliver AI solutions aligned with business needs. Deploy and monitor solutions in cloud environments (e.g., AWS SageMaker, GCP Vertex AI, Azure ML, REST(FAST API) with automated retraining and model health checks. Required Skills and Qualifications: Bachelors or Master’s degree in Computer Science, Machine Learning, Data Science, or related field. 3+ years of experience in AI/ML engineering, with proven success in both traditional predictive modelling and LLM-based development. Strong Python programming skills and familiarity with ML libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, and Transformers. Experience in parameter-efficient fine-tuning (PEFT) using frameworks such as Hugging Face PEFT, QLoRA, or AdapterHub. Proficiency in building MLOps workflows with tools like MLflow, Airflow, Kubeflow, or SageMaker Pipelines. Solid SQL/NoSQL experience and strong data wrangling skills. Hands-on experience deploying models in production cloud environments and containerized systems (e.g., Docker, Kubernetes). Excellent problem-solving, debugging, and communication skills.

We are seeking a hands-on, forward-thinking Machine Learning Technical Lead with deep expertise in traditional ML, NLP, Generative AI, and causal inference, and a strong understanding of multimodal large language models (LLMs) capable of processing both image and text data. The ideal candidate will lead the development, scaling, and evaluation of cutting-edge AI systems that deliver high business value from complex, high-volume datasets. This role involves team leadership, cloud-native ML deployment (AWS/Azure), statistical rigor, and clear communication of AI-driven insights to both technical and non-technical stake holders Key Responsibilities: Lead the design, development, and deployment of machine learning systems covering: Predictive modelling NLP tasks: NER, summarization, classification Generative AI: LLMs with prompt engineering and fine-tuning Causal inference and impact evaluation Multimodal modelling using vision-language models (e.g., CLIP, BLIP, GPT-4V) for use cases that involve image and text inputs Build and scale models that support impact evaluation, uplift modelling, and causal inference, using frameworks like Do Why, EconML, or CausalNex. Collaborate with stakeholders to define, quantify, and evaluate the causal impact of product interventions, policy changes, or ML-driven decisions. Architect scalable ML pipelines on AWS or Azure, handling high-throughput, multi-source data ingestion and model orchestration. Guide the integration of LLMs and prompt engineering into business workflows (e.g., classification, summarization, generative reasoning). Conduct deep exploratory data analysis (EDA) using statistical techniques: hypothesis testing, correlation analysis, regression diagnostics. Ensure robust MLOps practices including CI/CD, automated retraining, performance monitoring, and rollback strategies. Present AI findings, impact estimates, and strategic implications to technical peers, executives, and cross-functional partners. Mentor and manage a team of data scientists and ML engineers, fostering best practices and continuous innovation. Required Skills and Qualifications: Bachelors or Master’s in Computer Science, Statistics, Data Science, or related quantitative field. 6+ years of experience in AI/ML development, with 2+ years in a technical leadership capacity. Hands-on experience with: Predictive modelling (e.g., regression, XGBoost, tree-based models) NLP systems (e.g., NER, summarization, classification) Generative AI models (e.g., GPT, LLaMA) and prompt engineering Causal inference frameworks (e.g., DoWhy, EconML, Pyro) Strong statistical foundation with expertise in experimental design, counterfactual analysis, and impact evaluation. Proficiency in Python, PySpark, and libraries like scikit-learn, Hugging Face Transformers, and REST framework Candidate must be in Chennai or in the nearby districts, or in the nearby states of Kerala, Karnataka and willing to relocate to Chennai