Machine Learning Engineer (Remote)

Crossing Hurdles

Position:

Role Responsibilities:

• Design and implement scalable ML pipelines for model training, evaluation, and continuous improvement.
• Build and fine-tune deep learning models for reasoning, code generation, and real-world decision-making.
• Collaborate with data scientists to collect and preprocess training data.
• Develop benchmarking tools to test models across reasoning, accuracy, and speed.
• Implement reinforcement learning loops and self-improvement mechanisms for autonomous agent training.
• Work with systems engineers to optimize inference speed, memory efficiency, and hardware utilization.
• Maintain model reproducibility and version control through experiment-tracking systems.
• Contribute to cross-functional research efforts to improve model generalization and fine-tuning methods.
  

Requirements:

• Strong background in machine learning, deep learning, or reinforcement learning.
• Proficient in Python with experience in PyTorch, TensorFlow, or JAX.
• Understanding of training infrastructure, distributed training, and GPU/TPU-based workflows.
• Ability to build end-to-end ML systems including preprocessing, feature extraction, training, and deployment.
• Familiarity with MLOps tools such as Weights & Biases, MLflow, Docker, Kubernetes, or Airflow.
• Experience designing custom architectures or adapting LLMs, diffusion models, or transformer-based systems.
• Strong experimental reasoning and ability to evaluate model performance, bias, and generalization.
• Curiosity about AI agents and autonomous reasoning systems.
  

Key Domains:

• Machine Learning & Deep Learning:

  Neural networks, transformers, diffusion models, LLMs

• Reinforcement Learning:

  RL algorithms, agent training frameworks, self-improving systems

• AI Systems Engineering:

  Distributed training, GPU/TPU optimization, large-scale pipelines

• MLOps & Infrastructure:

  Experiment tracking, CI/CD for ML, containerization, orchestration

• Applied AI:

  Code generation models, reasoning systems, autonomous agent behavior

Application Process:

• Apply for the job role
• Await the official message/email from our recruitment team (typically within 12 days)