Machine Learning Engineer

Top Echelon Software, LLC; Austin (TX); Presencial; USD 120.000 - 170.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Employer-subsidized healthcare (med/ d

Pre-tax commuter benefits

Flexible Spending Account (FSA)

Employer-covered disability and life

401(k) retirement plan

Generous PTO

Covered lunches and more

Descripción de la vacante

NGV Talent in Austin, TX seeks an experienced Machine Learning Engineer to develop and deploy deep learning models for autonomous systems, including CNNs, Transformers, and MLLMs. You will manage datasets, training pipelines, and inference optimization to power safe navigation.

Responsibilities include model development, data curation, distributed training, and collaboration with cross-functional teams to deploy solutions on deployed platforms.

Formación

• Strong foundation in ML algorithms and neural networks.
• Experience in at least one domain such as computer vision, LLMs or generative AI.
• Minimum 3 years of neural network development, data collection, training and deployment.

Responsabilidades

• Develop and optimize ML models for environment understanding and road user prediction.
• Curate and manage large-scale datasets via collection, preprocessing and augmentation.
• Enhance training pipelines with distributed training, hyperparameter tuning, and monitoring.
• Improve deployment and efficiency through inference optimization and hardware adaptation.
• Explore cutting-edge DL techniques from recent research.
• Collaborate with researchers, software engineers and robotics experts to integrate solutions.

Conocimientos

Neural networks

Computer vision

Transformers

ML pipelines

Distributed training

Python

PyTorch

TensorFlow

JAX

PySpark

NumPy

SciPy

C++

SQL

Educación

Advanced degree in CS/ML/Robotics

Herramientas

PyTorch

TensorFlow

JAX

PySpark

NumPy

SciPy

C++

SQL

Descripción del empleo

Job Title:Machine Learning Engineer
Location:Austin, TX
Salary Range:$120,000 - $170,000 Per Year
Job Type:Direct Hire

Sponsorship:Yes, Company provides visa sponsorship

Job Overview

A leading autonomous mobility company seeks an experienced Machine Learning Engineer to develop and deploy deep learning models for autonomous vehicles and delivery robots. You will work on CNNs, Transformers, and MLLMs to power safe navigation, managing datasets, training pipelines, and inference optimization. This role drives innovation in self-driving technology, leveraging cloud platforms and collaborating across teams.

Key Responsibilities

• Develop and optimize machine learning models, including those for environmental understanding and road user intention prediction.

• Curate and manage large-scale datasets through collection, preprocessing, and augmentation.

• Enhance training pipelines with distributed training, hyperparameter tuning, and automated monitoring.

• Improve model deployment and efficiency via inference optimization and hardware adaptation.

• Explore and apply cutting-edge deep learning techniques from recent research.

• Collaborate with researchers, software engineers, and robotics experts to integrate solutions into autonomous systems.

Requirements

• Strong understanding of fundamental machine learning algorithms and neural network techniques.

• Expertise in at least one modern machine learning domain, such as computer vision, large language models, or generative AI.

• At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment.

• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, along with PySpark, NumPy, and SciPy.

• Working knowledge of C++ and SQL.

• Ability to quickly absorb new concepts from research papers, technical reports, and documentation.

• Strong collaboration and communication skills to align technical work with business objectives.

Preferred Qualifications

• Advanced degree in Computer Science, Machine Learning, Robotics, or a related field.

• Experience developing ML algorithms for autonomous vehicles or robotics applications.

• Familiarity with neural network deployment tools such as Triton or TensorRT.

• Proven ability to set and achieve mid- and long-term goals independently.

• Experience in cross-functional, multidisciplinary teams.

• Publications in top-tier ML conferences, patent contributions, or open-source ML projects.

Benefits

• Employer-subsidized healthcare (medical, dental, vision)

• Pre-tax commuter benefits

• Flexible Spending Account (FSA)

• Employer-covered disability and life insurance

• 401(k) retirement plan

• Generous PTO

• Covered lunches and more