Senior AI/ML Engineer

Join MSBC as an AI/ML Engineer – Deliver Real-World Intelligent Systems

At MSBC, we design and implement practical AI solutions that solve real business problems across industries. As an AI/ML Engineer, you will play a key role in building and deploying machine learning models and data-driven systems that are used in production. This role is ideal for engineers with solid hands-on experience delivering end-to-end AI/ML projects.

Key Tools and Frameworks

Programming Languages

Machine Learning Libraries

Data Pipelines

Model Deployment

Cloud Platforms

Version Control

Key Responsibilities

• Design and develop machine learning models to address business requirements.
• Build and manage data pipelines for training and inference workflows.
• Train, evaluate, and optimize models for accuracy and performance.
• Deploy models in production environments using containerized solutions.
• Work with structured and unstructured data from various sources.
• Ensure robust monitoring, retraining, and versioning of models.
• Contribute to architecture and design discussions for AI/ML systems.
• Document processes, results, and deployment procedures clearly.
• Collaborate with software engineers, data engineers, and business teams.
• Drive independent problem solving and experimentation to deliver innovative solutions.
• Work with open-source models – handling, deployment, fine-tuning, and optimization – especially for privacy-focused/on-prem deployments.
• Apply ML theory to design end-to-end AI architectures beyond simple API consumption.
• Contribute across multiple AI subdomains including NLP, Computer Vision, Signal/Audio Processing, and Multimodal systems.
• Stay ahead of emerging AI trends, demonstrating technical curiosity through self-driven projects, research, or open-source contributions.

Required Skills and Qualifications

• 4+ years of hands-on experience delivering ML solutions in production
• Proven track record across multiple AI subdomains (NLP, CV, Generative AI, Signal/Audio, Multimodal)
• Strong programming skills in Python with deep understanding of ML fundamentals
• Experience in supervised & unsupervised learning, regression, classification, clustering
• Practical expertise in open-source model handling, fine-tuning, optimization, and deployment
• Solid knowledge of data preprocessing, feature engineering, and model evaluation
• Experience with APIs, containers, and cloud platforms (AWS/GCP/Azure)
• Familiarity with

  C

  I/CD workflows and version control (Git)
• Self-driven, technically curious, and able to deliver in fast-paced environments
• Excellent
  English communication skills for collaboration with distributed teams
• Bachelor’s/Master’s in Computer Science, Data Science, Engineering, or related field