AI/Machine Learning Engineer

We are looking for a passionate and skilled Machine Learning Engineer to join our team. You will play a key role in building, deploying, and maintaining scalable ML models and pipelines, focusing on agentic AI, Video/Audio ML. This role involves close collaboration with data scientists, software engineers, and product teams to deliver intelligent solutions.

Key Responsibilities

  • Design, implement, and optimize multimodal AI models that integrate visual, audio, and language modalities.
  • Extend and fine-tune Vision-Language Models for perception and interaction tasks.
  • Build scalable ML pipelines for data preprocessing, training, validation, and deployment.
  • Develop agentic behaviors (reasoning loops, decision-making, memory, planning) integrated with vision and audio inputs.
  • Build and test custom algorithms for signal interpretation, scene understanding, and interactive tasks.
  • Collaborate with cross-functional teams to define business requirements and translate them into technical solutions.
  • Evaluate model performance across various benchmarks; optimize for accuracy, latency, and resource efficiency.
  • Duly document experiments, processes, and models for reproducibility and knowledge sharing.
  • Stay up-to-date with the latest advancements in agentic AI, multimodal learning, and cognitive architectures.

Required Qualifications

  • Bachelor’s or master’s degree in Electronic and Telecommunication Engineering, Computer Science, Data Science, Statistics, or a related field.
  • Proven experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or Keras.
  • Strong understanding of AI agent concepts.
  • Strong algorithm solving skills.
  • Strong programming skills in Python.
  • Solid understanding of ML/DL model architectures, algorithms, signal processing, statistics, probability, and data structures.
  • Familiarity with cloud platforms such as AWS, GCP, or Azure and on-premise server configurations for model deployment.
  • Knowledge of containerization tools like Docker and orchestration tools like Kubernetes is a plus.
  • Experience working with MLOps tools (e.g., MLflow, SageMaker, Vertex AI) is an added advantage.
  • Excellent problem-solving and communication skills.

Desirable Skills (Nice to have)

  • Experience with core contributions to ML model architecture modifications.
  • Familiarity with big data tools (Spark, Hadoop).
  • Exposure to CI/CD pipelines for ML model deployment.
  • Contributions to open-source ML projects or participation in algorithm/AI competitions.

What We Offer

  • Opportunity to work on cutting-edge ML/AI projects
  • Collaborative and innovation-driven work environment
  • Continuous learning and development support
  • Competitive compensation and benefits

    Scroll to Top