Job Description

Description
As an AI/ML Engineer, you will be responsible for designing, developing, and implementing intelligent systems and machine learning models to solve complex real-world problems. You will collaborate with cross-functional teams to collect and analyze data, build predictive models, and deploy scalable AI-driven solutions. This role requires strong programming skills, applied knowledge of machine learning frameworks, and a passion for innovation and research in Artificial Intelligence.


Responsibilities
You will be working as an AI/ML Engineer, closely collaborating with Data Scientists, Software Developers, and Business Analysts to build and optimize machine learning applications. You would be required to participate in design discussions, technical sessions, and performance evaluations.


Your Responsibilities will include:


Design and develop machine learning models and algorithms for diverse applications such as Natural Language Processing (NLP), Computer Vision, Large Language Models (LLMs), and predictive analytics. Develop RAG (Retrieval-Augmented Generation) based applications. Collect, preprocess, and analyze data from multiple sources to train and evaluate ML models. Implement and optimize AI/ML models for deployment on cloud or edge platforms. Collaborate with software development teams to integrate ML components within web applications using frameworks like Django, Flask, or FastAPI. Evaluate model performance using metrics such as accuracy, precision, recall, and F1 score. Apply software engineering best practices including version control, code review, and automated testing to ensure scalable, high-quality solutions. Stay up to date with the latest advancements in AI/ML research and apply innovative approaches to improve model performance and efficiency. Required Skills

Primary Technical Skills:

Bachelor's or Master's Degree in Computer Science, Data Science, or a related field. 3+ years of experience in AI/ML model design, development, and deployment. Strong programming skills in Python (experience with R or MATLAB is an advantage). Hands-on experience with popular AI/ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn. Experience with web frameworks like Django, Flask, or FastAPI. Strong understanding of statistical modeling, NLP, LLMs, and computer vision techniques. Proficiency in data preprocessing, visualization, and analysis tools like Pandas, NumPy, and Matplotlib. Sound knowledge of linear algebra, calculus, probability, and hypothesis testing. Strong problem-solving ability and the capability to work independently or as part of a team. Excellent communication skills to explain technical concepts to non-technical stakeholders.

Secondary Technical Skills:

Experience with AWS, Azure, or Google Cloud for AI/ML model deployment. Familiarity with distributed computing, parallel processing, and cloud architecture. Experience with data scraping tools such as Requests, Selenium, or Scrapy. Understanding of data management, relational databases, and SQL. * Exposure to Agile methodologies, CI/CD pipelines, and DevOps practices.