Talantix.io
Trase Systems•18.02.26
AI SCORE 8.5

Senior AI/​ML Engineer - Applied Machine Learning (Remote)

$100K–$150K/year
RemoteAI/Big Data
Python•Machine Learning•TensorFlow•PyTorch•scikit-learn•Statistical Modeling•Data Structures

About the Role

We are seeking a Senior AI/ML Engineer - Applied Machine Learning to join our innovative team at Trase Systems. As a remote AI/ML Engineer, you will play a crucial role in empowering enterprise leaders to harness the full potential of AI while minimizing complexity and risks. This position offers an exciting opportunity to work with cutting-edge technologies and contribute to mission-critical applications across various industries.

What You'll Do

  • Design and implement advanced machine learning models to solve complex problems in industries such as Healthcare, Oil & Gas, and National Security.
  • Collaborate with cross-functional teams to develop AI solutions that drive efficiency and cost savings.
  • Optimize AI deployment and management processes to enhance performance and scalability.
  • Stay updated with the latest advancements in AI and machine learning technologies and apply them to our platform.
  • Contribute to the development of agentic applications that leverage AI for improved decision-making.

Requirements

  • 5+ years of experience in AI/ML engineering, with a strong focus on applied machine learning.
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Strong understanding of data structures, algorithms, and statistical modeling.
  • Excellent problem-solving skills and the ability to work independently in a remote environment.

Nice to Have

  • Experience in deploying AI solutions in enterprise environments.
  • Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.
  • Knowledge of natural language processing (NLP) and computer vision techniques.

What We Offer

  • Competitive salary ranging from $100,000 to $150,000 per year.
  • Fully remote work environment with flexible hours.
  • Opportunities for professional growth and development in the AI field.
  • Collaborative and innovative team culture.
  • Health and wellness benefits to support your well-being.
Why This Job8.5 of 10

This Senior AI/ML Engineer role at Trase Systems offers a unique opportunity to work remotely on cutting-edge AI applications with a competitive salary.

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

Who Will Succeed Here

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Proficient in Python and experienced with frameworks like TensorFlow and PyTorch, demonstrating the ability to build and deploy complex machine learning models efficiently.

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Self-motivated and comfortable in a remote work environment, showcasing strong time management and collaboration skills using tools like Slack and GitHub to maintain productivity and communication.

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Deep understanding of statistical modeling and data structures, with a mindset focused on continuous learning and experimentation to innovate and optimize machine learning algorithms.

Learning Resources

→Python Data Science Handbookguide
→Deep Learning Specialization by Andrew Ngcourse
→Machine Learning with Python: A Practical Introductionarticle

Career Path

Senior AI/ML Engineer - Applied Machine Learning(Now)→Lead AI/ML Engineer(1-2 years)→AI/ML Architect(3-5 years)

Market Overview

Market Size 2024
$41B
Annual Growth
24.2%
AI Adoption
80%
Investment
+300%
Labour Demand
+35%
Avg Salary
$150K

Skills & Requirements

Required
PythonMachine LearningTensorFlow
Growing in Demand
Deep LearningNatural Language ProcessingBig Data Technologies
Declining
R ProgrammingMatlab

Domain Trends

Increased Demand for Explainable AI
As organizations adopt AI, the need for transparency in AI decision-making is growing, with 65% of companies prioritizing explainability in their AI systems.
Shift Towards Automated Machine Learning (AutoML)
The AutoML market is projected to grow by 35% annually, as businesses seek to simplify and accelerate the deployment of machine learning models.
Integration of AI in Edge Computing
With the rise of IoT devices, 45% of enterprises are implementing AI at the edge to enhance real-time data processing and analytics.

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