AI / ML Engineer

Job Description

Immediate Joiner wanted

Job Description:
• Design and develop scalable machine learning models and deploy them in production environments.

• Build and implement agentic systems that can autonomously analyze tasks, process large volumes of unstructured data, and provide actionable insights.

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

. • Develop deterministic and reliable AI systems to address real-world challenges.

• Create and optimize scalable, distributed ML pipelines.

• Perform data preprocessing, feature engineering, and model evaluation to ensure high performance and reliability.

• Stay abreast of advancements in AI technologies and incorporate them into business solutions.

• Participate in code reviews, contribute to system architecture discussions, and continuously enhance project workflows.

Required Skills and Qualifications

• Software Engineering Fundamentals: Strong foundation in algorithms, data structures, and scalable system design.

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or related fields with a solid academic track record

. • Experience: 2-5 years of hands-on experience in building AI systems or machine learning applications

. • Agentic Systems: Proven experience in developing systems that utilize AI agents for automating complex workflows, analyzing unstructured data, and generating actionable outcomes

. • Programming: Proficiency in programming languages such as Python, Java, or Scala.

• AI Expertise: Experience with machine learning frameworks like TensorFlow, PyTorch, or Hugging Face libraries (e.g., for working with transformer-based models and LLMs).

• MLOps Knowledge (preferred): Familiarity with tools like MLflow, Kubeflow, Airflow, Docker, or Kubernetes

. • Cloud Platforms: Hands-on experience with AWS, Azure, or Google Cloud for deploying machine learning models.

• Big Data: Experience with data processing tools and platforms such as Apache Spark or Hadoop

. • Problem-Solving: Strong analytical and problem-solving skills, with the ability to create robust solutions for complex challenges

. • Collaboration and Communication: Excellent communication skills to articulate technical ideas effectively to both technical and non-technical stakeholders.”