AI Developer

Job Overview

The AI Developer will play a crucial role in building, deploying, and optimizing AI models, focusing primarily on Generative AI, Machine Learning (ML), and other advanced AI techniques. This hands-on role involves working closely with data scientists, engineers, and cross-functional teams to develop and implement AI solutions that address key business challenges and support strategic initiatives.

Key Job Responsibilities

• Design, build, and implement AI solutions using Generative AI, Machine Learning, and other advanced AI techniques to solve complex business problems.
• Collaborate with data science and engineering teams to gather requirements, understand objectives, and design solutions that align with business goals.
• Participate in brainstorming sessions to identify new solutions and potential improvements.
• Train, fine-tune, validate, and optimize machine learning models for performance, scalability, and accuracy.
• Ensure that models are production-ready, robust, and capable of meeting operational demands.
• Work with data engineers to collect, preprocess, and clean structured as well as unstructured data for model development.
• Apply data augmentation, feature engineering, and transformation techniques to enhance data quality and improve model performance.
• Deploy AI models to production, monitor their performance, and work with the engineering team to implement feedback loops and continuous improvements.
• Troubleshoot and address issues with deployed models, ensuring high availability, reliability, and scalability.
• Stay up-to-date with the latest advancements in AI, particularly in Generative AI and ML, to recommend new tools and techniques.
• Conduct experiments to validate model approaches, optimizing for impact, efficiency, and business value.
• Document model development and deployment processes, code, and performance metrics.
• Promote best practices in AI development, including reproducibility, modularity, and adherence to ethical AI guidelines.

Qualifications/Requirements

Educational Background:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Relevant certifications in AI, ML, or data science are a plus.

Experience:

• 3+ years of experience in developing and deploying machine learning and AI models, preferably in an industrial or manufacturing context.
• Strong hands-on experience with Generative AI models(e.g., Foundational and Multimodal models, Image and Video generation models) and machine learning libraries (e.g., PyTorch, TensorFlow, Keras, Scikit-Learn, OpenCV).
•  Experience with Microsoft CoPilot Studio, OpenAI tools and API’s for GPT creation, Hugging Face, LangChain, LangGraph, Large Language Model’s, Generative AI or similar tools.
•  Experience with DevOps practices, in the context of AI and ML model deployment.
•  Experience with SQL and NoSQL databases and basic data manipulation.

Technical Skills:

• Proficiency in Python, SQL, and relevant AI/ML libraries and frameworks.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps tools for model deployment and monitoring.
• Solid understanding of machine learning algorithms, natural language processing, computer vision, recommendation systems, and deep learning architectures.
• Familiarity with data preprocessing techniques and tools for handling large datasets.
• Familiarity with data visualization tools like Matplotlib, Seasborn, or Tableau.
• Familiarity with RAG method (including advanced RAG techniques) and AI Agentic patterns.
•  Familiarity with AI observability, performance tracking, troubleshooting hallucinations in models.

Soft Skills & Competencies:

• Strong analytical and problem-solving skills, with a focus on practical, real-world applications.
• Excellent communication skills, with the ability to collaborate effectively with cross-functional teams.
• Ability to work in a fast-paced, agile environment and manage multiple projects simultaneously.

Additional Information