Machine Learning Roles we Recruit for

Machine Learning Engineer

Responsibilities:

  • General machine learning algorithms and approaches.
  • Supervised and unsupervised learning.
  • Ensemble and batch learning.

Deep Learning Engineer

Responsibilities:

  • Neural networks, CNNs, RNNs, LSTMs, GRUs.
  • Autoencoders, GANs, VAEs.
  • Deep reinforcement learning.

NLP Scientist

Responsibilities:

  • Natural Language Processing.
  • Speech Recognition.
  • RL in NLP.

Computer Vision Engineer

Responsibilities:

  • Image and video analysis.
  • CNNs in Computer Vision.
  • RL in Computer Vision.

Reinforcement Learning Specialist

Responsibilities:

  • Policy gradient methods, Q-Learning, TD Learning.
  • Hierarchical and inverse reinforcement learning.
  • Application-specific RL (games, robotics, finance, healthcare, autonomous vehicles).

Data Scientist

Responsibilities:

  • Time series analysis.
  • Anomaly detection.
  • Clustering and dimensionality reduction.
  • Recommender systems.

Algorithm Engineer

Responsibilities:

  • Evolutionary algorithms.
  • Fuzzy logic and genetic programming.
  • Quantum machine learning.

AI Ethics and Fairness Officer

Responsibilities:

  • Explainable AI and Interpretable machine learning.
  • Fairness in machine learning and Ethical AI.

Edge AI Developer

Responsibilities:

  • Federated Learning.
  • Edge AI and TinyML.

Robotic Process Automation Developer

Responsibilities:

  • Automating rule-based tasks.
  • Workflow automation.

AI Research Scientist (Meta-Learning)

Responsibilities:

  • Meta-learning, multi-task learning, and one-shot learning.
  • Neural architecture search and capsule networks.

AI Research Scientist (Multi-modal Learning)

Responsibilities:

  • Integrating data and models from multiple modalities.
  • Few-shot, zero-shot, and continuous learning.