Autonomous AI Systems Machine Learning Engineer

Nova Kore

You'll build and deploy advanced AI agents, shaping the future of autonomous systems.

Compensation:

USD 14/hour

Location:

Remote: India

Mission of Nova Kore:

"Connecting people and companies to create meaningful, transformative career and business opportunities."

What makes you a strong candidate:

• You are proficient in Version control, TensorFlow, Python, PyTorch, Model evaluation, Machine learning, MLOps, Learning strategies.
• English - Conversational

Responsibilities and more:

Machine Learning Engineer - India

The company is hiring a machine learning engineer to design, train, and deploy large-scale learning systems that power autonomous AI agents for an AI lab partner. This role is ideal for engineers interested in building models capable of reasoning, adapting, and performing complex tasks in real-world environments. The position operates at the intersection of machine learning research, systems engineering, and AI agent behavior, translating ideas into robust and scalable learning pipelines.

Candidate profile

* Strong background in machine learning, deep learning, or reinforcement learning.

* Proficiency in Python and familiarity with frameworks such as PyTorch, TensorFlow, or JAX.

* Understanding of training infrastructure, including distributed training, GPUs or TPUs, and data pipeline optimization.

* Ability to implement end-to-end machine learning systems, from preprocessing and feature extraction to training, evaluation, and deployment.

* Experience with MLOps tools such as Weights & Biases, MLflow, Docker, Kubernetes, or Airflow.

* Experience designing custom architectures or adapting large language models, diffusion models, or transformer-based systems.

* Ability to evaluate model performance, generalization, and bias using data-driven experimentation.

* Interest in AI agents and model-driven simulation of reasoning, problem-solving, and collaboration.

Primary goal of the role

To develop, optimize, and deploy machine learning systems that improve agent performance, learning efficiency, and adaptability through advanced architectures, training workflows, and evaluation pipelines.

What you’ll do

* Design and implement scalable machine learning pipelines for training, evaluation, and continuous improvement.

* Build and fine-tune deep learning models for reasoning, code generation, and real-world decision-making.

* Collaborate on data collection and preprocessing to ensure training data quality and representativeness.

* Develop benchmarking tools to evaluate models across reasoning, accuracy, and performance speed.

* Implement reinforcement learning loops and self-improvement mechanisms for agent training.

* Optimize inference speed, memory efficiency, and hardware utilization in collaboration with systems engineers.

* Maintain model reproducibility and version control using experiment tracking systems.

* Contribute to cross-functional research initiatives focused on learning strategies, fine-tuning methods, and generalization performance.

Pay and work structure

* Hourly contractor role.

* Weekly payments via Stripe Connect based on hours logged.

* Part-time commitment of 20 to 40 hours per week.

* Fully remote and asynchronous work with flexible scheduling.

* Weekly bonus ranging from $500 to $1000 USD per 5 tasks created.