Machine Learning Engineer: Computer Vision in Production

MORSE Corp; Arlington (VA); On-site; USD 90,000 - 210,000; Full time

Benefits offered by this job

10 paid holidays per year

Open leave policy

Bonus and stock options

401(k) match

Job summary

MORSE Corp is seeking a Machine Learning Engineer to design, implement, and manage ML algorithms with a focus on computer vision and other data modalities. You will acquire truth data, integrate and test algorithms, review literature, and transition models to production on on-prem, cloud, or embedded systems.

The role involves staying current with LLMs, audio, CV, and reasoning methods, collaborating with a team of engineers to deliver mission-critical AI for US National Security customers.

Qualifications

• Master's or PhD in CS/CE/DS or related field.
• US citizenship and ability to obtain security clearance.
• Proven experience applying CV models and libraries.
• Proficiency in Python.
• Experience with cloud platforms AWS/Azure.
• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.

Responsibilities

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.
• Use MLOps tools for efficient experiment tracking, data management, and reproducibility
• Write robust, efficient, and maintainable code
• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models

Skills

Python programming

Strong communication

Team collaboration

Education

Master's or PhD in CS/CE/DS or related field

Tools

Docker

AWS

Azure

Airflow

MLFlow

AimStack

Job description

MORSE Corp is seeking a Machine Learning Engineer to design, implement, and manage ML algorithms with a focus on computer vision and other data modalities. You will acquire truth data, integrate and test algorithms, review literature, and transition models to production on on-prem, cloud, or embedded systems.

The role involves staying current with LLMs, audio, CV, and reasoning methods, collaborating with a team of engineers to deliver mission-critical AI for US National Security customers.