Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. Gather, clean, and prepare large datasets to ensure readiness for AI model training Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. Lead and mentor team members to improve performance. Collaborate with operations, architects, and product teams to resolve issues and define product designs. Exercise best practices in agile development and software engineering. Code, unit test, debug and perform integration tests of software components Participate in software design reviews, code reviews and project planning. Write and review documentation and technical blog posts. Contribute to department attainment of organizational objectives and high customer satisfaction Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Minimum 4+ years of hands-on experience developing AI-based applications using Python. Experience using deep learning frameworks (TensorFlow, PyTorch, or Keras) Experience in Pydantic Solid understanding of ML/AI concepts:EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. Familiarity with Natural Language Processing (NLP) techniques. Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations. Proven expertise in integrating and working with LLMs to build robust AI solutions. Skilled in crafting effective prompts to guide LLMs to provide desired outputs. Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc., Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. Proficient in microservices development using Python (Django/Flask or similar technologies). Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders Preferred technical and professional experience Experience in MLOPs frameworks (BentoML,Kubeflow or similar technologies) and exposure to LLMOPs Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. Understanding of security and ethical best practices for data and model development Contributions to open source projects Experience in Agile development methodologies Familiarity with platforms like Kubernetes and experience building on top of the native platforms Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s) <

Location: Vishakapatnam Andhra Pradesh India Duration: 1 year Job Description We are looking for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field. Responsibilities Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress Managing available resources such as hardware, data, and personnel so that deadlines are met Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Finding available datasets online that could be used for training Defining validation strategies Defining the preprocessing or feature engineering to be done on a given dataset Defining data augmentation pipelines Training models and tuning their hyperparameters Analyzing the errors of the model and designing strategies to overcome them Deploying models to production Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks Stay up to date with developments in the machine learning industry Skills Proficiency with a deep learning framework such as TensorFlow or Keras Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas Familiarity with data structures, data modeling, and software architecture Expertise in visualizing and manipulating big datasets Proficiency with OpenCV Familiarity with Linux Ability to select hardware to run an ML model with the required latency