Machine Learning Roles we Recruit for
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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.