Machine Learning Algorithm Engineer

Intelliswift - An LTTS Company; Redmond (WA); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Intelliswift - An LTTS Company is seeking a Machine Learning Algorithm Engineer in Redmond, WA, blended hybrid work with three days onsite. The role focuses on developing and deploying ML algorithms for intelligent sensing systems and hardware-integrated AI solutions.

You will work on ML pipelines, model training, and optimization for edge devices, collaborating with a multidisciplinary team to deliver prototype systems.

Qualifications

• Bachelor’s degree in a technical field (CS/Math/EE/Robotics) with 1–6 years in ML/algorithm development.
• Strong Python programming and ML/deep learning experience.
• Hands-on with PyTorch and/or TensorFlow; C++ OO programming experience.

Responsibilities

• Design, develop, test, and optimize ML and DL algorithms.
• Build and improve ML pipelines for hardware deployment.
• Develop models and algorithms for data analysis and performance.
• Train, evaluate, and fine-tune models with modern ML frameworks.
• Troubleshoot software and algorithm performance issues.
• Collaborate with multidisciplinary teams to prototype solutions.
• Deploy ML to embedded/edge environments; improve deployment workflows.
• Work independently from concept to implementation.

Skills

Python programming

PyTorch

TensorFlow

C++

ML algorithms

Research

Independent work

Education

Bachelor's degree in CS/Math/EE/Robotics

Master's degree preferred

Tools

Embedded systems toolchains

AI accelerators familiarity

Job description

Job Title: Machine Learning Algorithm Engineer

Location: Redmond, WA (Hybrid - 3 Days Onsite)

Duration: 12-Month Contract (Potential for Extension)

We are seeking a Machine Learning Algorithm Engineer to join an innovative research and engineering team focused on intelligent sensing systems, machine learning, and hardware-integrated AI solutions. This role involves developing, optimizing, and deploying machine learning algorithms that operate on real-world sensor data and support the development of advanced prototype systems.

The ideal candidate combines strong Python development skills with hands‑on experience in machine learning, deep learning frameworks, and deploying AI solutions to hardware platforms

Responsibilities

• Design, develop, test, and optimize machine learning and deep learning algorithms.
• Build and improve ML pipelines for deployment on hardware platforms.
• Develop statistical models and algorithms for data analysis and performance optimization.
• Train, evaluate, and fine‑tune machine learning models using modern ML frameworks.
• Troubleshoot and resolve software and algorithm performance issues.
• Collaborate with multidisciplinary engineering teams to develop prototype solutions.
• Deploy AI and machine learning solutions to embedded and edge‑computing environments.
• Improve software efficiency, scalability, and deployment workflows.
• Work independently to execute projects from concept through implementation.

Required Qualifications

• Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, Robotics, or a related technical field. Master's degree preferred.
• 1-6 years of professional experience in machine learning, AI, software engineering, or algorithm development.
• Strong programming skills in Python.
• Experience developing machine learning and deep learning algorithms.
• Hands‑on experience with PyTorch and/or TensorFlow.
• Experience with object‑oriented programming using C++ or similar languages.
• Familiarity with AI‑assisted development tools and workflows.
• Ability to work independently in a research‑oriented environment.

Preferred Qualifications

• Experience with embedded systems and edge‑computing platforms.
• Experience deploying machine learning models to hardware environments.
• Understanding of firmware concepts and hardware/software integration.
• Experience working with ARM‑based computing architectures and AI accelerators.
• Knowledge of machine learning deployment optimization techniques