Talantix.io
Remote Position•08.03.26
AI SCORE 8.5

Senior Machine Learning Engineer II - Remote

$140K–$180K/year
RemoteAI/Big Data
Machine Learning•Python•Java•TensorFlow•PyTorch•Cloud Services•NLP•Computer Vision

About the Role

We are seeking a talented Senior Machine Learning Engineer II - Remote to join our innovative team. In this role, you will leverage your expertise in machine learning and data science to develop cutting-edge solutions that drive our business forward. As a Senior Machine Learning Engineer, you will work collaboratively with cross-functional teams to design, implement, and evaluate machine learning models that enhance our product offerings.

What You'll Do

  • Design and implement machine learning algorithms and models for various applications.
  • Collaborate with data scientists and software engineers to integrate machine learning solutions into production systems.
  • Evaluate and optimize model performance using advanced metrics and techniques.
  • Utilize cloud services and distributed systems to scale machine learning applications.
  • Participate in code reviews and contribute to team knowledge sharing.

Requirements

  • 5+ years of experience as a Machine Learning Engineer or in a related role.
  • Strong proficiency in Python and Java, with experience in ML frameworks such as TensorFlow or PyTorch.
  • Solid understanding of data systems, APIs, and system design principles.
  • Experience with cloud services (AWS, Azure, or Google Cloud) and ML Ops practices.
  • Familiarity with NLP, computer vision, and deep learning techniques.

Nice to Have

  • Experience in product management or collaboration with marketing and sales teams.
  • Knowledge of compliance and analytics in software development.
  • Experience with performance management and employee relations.

What We Offer

  • A flexible work environment that promotes work-life balance.
  • Opportunities for professional growth and development.
  • A collaborative team culture that values innovation and creativity.
  • Access to cutting-edge technology and resources.
  • Competitive salary and benefits package.
Why This Job8.5 of 10

This Senior Machine Learning Engineer II role offers a unique opportunity to work remotely with cutting-edge technology in a collaborative environment.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

→

Proficient in implementing machine learning algorithms using Python and libraries such as TensorFlow and PyTorch, with hands-on experience in deploying models on cloud platforms like AWS or Google Cloud.

→

Strong understanding of Natural Language Processing (NLP) and Computer Vision techniques, capable of developing innovative solutions for real-world applications while working independently in a fully remote environment.

→

Demonstrates a growth mindset with at least 5 years of experience in machine learning, able to mentor junior engineers and contribute to architectural discussions while adapting to rapid technological advancements.

Learning Resources

→Deep Learning with Python and PyTorchcourse
→Machine Learning Crash Courseguide
→Natural Language Processing with Transformersarticle

Career Path

Senior Machine Learning Engineer II - Remote(Now)→Lead Machine Learning Engineer(2-4 years)→Director of Machine Learning(5-7 years)

Market Overview

Market Size 2024
$34.6B
Annual Growth
41.0%
AI Adoption
90%
Investment
+300%
Labour Demand
+36%
Avg Salary
$150K

Skills & Requirements

Required
Machine LearningPythonJava
Growing in Demand
Deep LearningMLOpsData Engineering
Declining
RSAS

Domain Trends

Increased Demand for Explainable AI
As organizations adopt AI, the need for transparency in machine learning models is rising, with 65% of companies prioritizing explainable AI solutions.
Integration of Machine Learning with Cloud Services
The market for cloud-based machine learning services is expected to grow by 45% annually as companies shift to cloud for scalability and efficiency.
Focus on Ethical AI Practices
78% of businesses are implementing ethical guidelines for AI development to address biases and ensure fairness in machine learning applications.

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