Hybrid AI/ML Engineer (2670) na Wissen Infotech

Experience: 3-6 years About Wissen Infotech Wissen Infotech has been a trusted leader in the IT Services industry for over 25 years, delivering high-quality solutions to a global clientele. Within Wissen, the AI Center of Excellence (AI-CoE) was conceptualized to drive cutting-edge research and innovation, enabling us to build our own products and intellectual property. This team focuses on solving complex business challenges using AI while setting new benchmarks for reliable and scalable AI solutions.

Position Overview: We're seeking AI Engineers with a strong focus on agentic systems to join our AI-CoE team. This is a unique opportunity for engineers driven to design, develop, and deploy robust, production-grade AI solutions. You'll play a pivotal role in building sophisticated AI[1]powered systems, leveraging state-of-the-art technologies to create scalable and reliable distributed solutions that autonomously analyze, process, and act on complex information, while ensuring a seamless user experience.

Key Responsibilities:

·         Design, develop, and deploy production-grade AI systems that can autonomously analyze complex tasks, process vast volumes of unstructured data, and generate actionable insights

·         Rigorously evaluate and test agentic systems to ensure their reliability, robustness, and deterministic behavior in real-world scenarios.

·         Collaborate closely with data scientists, software engineers, and domain experts to seamlessly integrate advanced AI capabilities into cutting-edge products and solutions

·         Develop and optimize scalable, distributed ML pipelines that support the lifecycle of complex AI deployments, from data ingestion to model deployment and monitoring.

·         Implement mechanisms for gathering and incorporating feedback from end[1]users to drive continuous improvement and refine the performance of deployed systems, ensuring a seamless user experience.

·         Stay at the forefront of advancements in AI, particularly in the realm of large language models (LLMs), autonomous systems, and their application in intelligent agents, integrating these innovations into our business solutions.

·         Actively participate in code reviews, contribute significantly to system architecture discussions, and continuously enhance project workflows to ensure best practices in building and deploying advanced AI.

Required Skills and Qualifications:

·         Software Engineering Fundamentals: Strong foundation in algorithms, data structures, and scalable system design, with a proven ability to build robust and maintainable software.

·         Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field with a solid academic track record.

·         Experience: 3+ years of hands-on experience in building and deploying production[1]grade AI systems or machine learning applications, with a distinct emphasis on architectures enabling autonomous behavior.

·         Agentic Systems & AI Agents: Demonstrated proven experience in designing, developing, and deploying systems that utilize AI agents for automating complex workflows, performing advanced analysis on unstructured data, and generating actionable, reliable outcomes in a production setting.

·         Agent Orchestration Frameworks: Must have hands-on experience with Langgraph or an equivalent agent orchestration framework (e.g., CrewAI, Autogen, Marvin) for building and managing multi-agent systems.

·          Evaluation & Reliability: Proven ability to rigorously evaluate the performance and reliability of complex AI systems, identify failure modes, and implement solutions for continuous improvement.

·          User-Centric Development: Experience in incorporating user feedback and iteratively refining AI systems to enhance user experience and system effectiveness.

·          Programming Proficiency: Expert-level proficiency in programming languages such as Python, for building scalable backend systems.

·          AI/ML Frameworks: Strong experience with machine learning frameworks like TensorFlow, PyTorch, or Hugging Face libraries, specifically for working with transformer-based models and Large Language Models (LLMs), and leveraging them within intelligent system architectures.

·          MLOps & Production Deployment: Practical experience with MLOps tools and practices (e.g., LangSmith, MLflow, Kubeflow, Airflow, Docker, Kubernetes) for orchestrating, deploying, monitoring, and maintaining production AI systems.

·          Cloud Platforms: Hands-on experience with major cloud platforms (AWS, Azure, or Google Cloud) for deploying, scaling, and managing machine learning models and distributed systems.

·          Problem-Solving: Exceptional analytical and problem-solving skills, with a strong ability to architect and implement robust, deterministic solutions for complex, real[1]world challenges involving autonomous AI.

• Collaboration and Communication: Excellent communication skills to articulate complex technical ideas effectively to both technical and non-technical stakeholders, fostering a collaborative environment.

What We Offer :

• An unparalleled opportunity to work with cutting-edge AI technologies, specifically in the rapidly evolving field of intelligent agents, and solve challenging business problems that have real-world impact.

• A collaborative, innovative, and inclusive work culture that encourages continuous learning and pushes the boundaries of AI research