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ML Engineer


WalkingTree Technologies


Location

Agra | India


Job description

Position Overview

As a machine learning engineer, you will lead our customer-facing machine learning initiatives and the customization of our foundation models for challenging real-life robotics tasks. A crucial aspect of the role is to interface with our Simulation Engineering Team and Foundation Model Research Team to adapt our cutting-edge models and high fidelity data pipelines to result in task-specific modules.

Key Responsibilities

Machine Learning Engineering:

Model Development: Implement and adapt machine learning models tailored for computer vision and robotics applications.

Data Strategy: Formulate data collection and acquisition strategies for both synthetic and real life data for model training.

Performance Tuning: Continuously review and fine-tune models based on evolving data and customer feedback, and make use of effective MLOps practices.

Technical Leadership: Collaborate closely with the engineering teams to uphold machine learning and software engineering best practices.

Simulation Interface: Work with our team of simulation engineers to customize the simulation platform based on customer requirements for data generation or model evaluation.

Foundation Model Collaboration: Interface with the Foundation Model Research Team to establish the base models that will be fine-tuned to meet customer specifications.

Research: Keep abreast of the latest developments in machine learning and robotics to maintain our competitive edge.

Requirements

Bachelor’s degree or above in Computer Science, Robotics, or a related field. (Master’s preferred).

A minimum of 4 years’ experience in machine learning, with a focus on robotics preferred.

Must have hands on experience with Pytorch, Python, Opencv, Computer vision, Neural Network.

In-depth understanding of machine learning algorithms, data structures, and performance tuning.

Familiarity with programming languages such as Python, C++, or Java.

Exceptional problem-solving abilities, with a knack for translating real-world problems into machine learning tasks.


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