Machine Learning Engineer

Crossing Hurdles is seeking a skilled Machine Learning Engineer for an hourly contract position, offering flexible, part-time work remotely within India. This role is ideal for individuals passionate about AI and looking to contribute to cutting-edge research and development.

Position: Machine Learning Engineer
Type: Hourly Contract
Compensation: INR 14 per hour (Estimated 5-15 Lacs PA based on full-time equivalent)
Location: India (Remote)
Commitment: Part-time, flexible

Responsibilities:

• Develop and deploy robust, scalable machine learning pipelines for model training, evaluation, and continuous improvement.
• Construct and refine deep learning models for advanced reasoning, code generation, and real-world decision-making applications.
• Partner with data scientists to curate and preprocess high-quality training datasets.
• Create and implement comprehensive benchmarking tools to assess model reasoning, accuracy, and performance speed.
• Integrate reinforcement learning loops and self-improvement mechanisms to train autonomous AI agents.
• Collaborate with systems engineers to optimize model inference speed, memory usage, and hardware efficiency (GPU/TPU).
• Ensure model reproducibility and maintain version control using experiment-tracking platforms.
• Contribute to cross-functional research initiatives aimed at enhancing model generalization and fine-tuning strategies.

Qualifications:

• A strong foundation in machine learning, deep learning, or reinforcement learning principles.
• Proficiency in Python, with hands-on experience in frameworks like PyTorch, TensorFlow, or JAX.
• Familiarity with training infrastructure, distributed training methodologies, and GPU/TPU-based computational workflows.
• Demonstrated ability to build end-to-end ML systems, encompassing preprocessing, feature engineering, training, and deployment.
• Experience with MLOps tools such as Weights & Biases, MLflow, Docker, Kubernetes, or Airflow.
• Proven experience in designing custom neural network architectures or adapting large language models (LLMs), diffusion models, or transformer-based systems.
• Excellent experimental design and analytical skills for evaluating model performance, identifying bias, and assessing generalization capabilities.
• A keen interest in AI agents and autonomous reasoning systems.

Areas of Expertise:
Candidates with specialization in the following domains are highly encouraged to apply:

• Machine Learning & Deep Learning: Expertise in neural networks, transformers, diffusion models, and LLMs.
• Reinforcement Learning: Strong understanding of RL algorithms, agent training frameworks, and self-improving systems.
• AI Systems Engineering: Experience with distributed training, GPU/TPU optimization, and large-scale ML pipelines.
• MLOps & Infrastructure: Familiarity with experiment tracking, CI/CD for ML, containerization, and orchestration tools.
• Applied AI: Experience in code generation models, reasoning systems, and developing autonomous agent behaviors.

Application Process:

• Submit your application for the role.
• Kindly await official communication from our recruitment team, which typically arrives within 1-2 business days.