Talantix.io
Mobiskill•30.01.26
AI SCORE 8.2

Senior Machine Learning Engineer - Retail Industry

$90K–$120K/year
RemoteAI/Big DataWW
Machine Learning•XGBoost•Pandas•scikit-learn•Data Analysis•Feature Engineering

About the Role

We are seeking a Senior Machine Learning Engineer to join our innovative startup focused on developing AI solutions for the retail industry. This Senior Machine Learning Engineer remote position offers you the chance to work on cutting-edge technology aimed at reducing waste in major retail operations.

What You'll Do

  • Design, train, and deploy machine learning models that address real business challenges.
  • Continuously improve model performance (accuracy, robustness, scalability) through rigorous experimental approaches.
  • Collaborate closely with product, data, and engineering teams to transform business needs into actionable ML solutions.
  • Participate in the industrialization of models and their integration into production systems.
  • Establish feature engineering pipelines, monitoring, and performance tracking.
  • Analyze model results, explain them to stakeholders, and recommend data-driven actions.
  • Contribute to defining best practices in ML and explore new algorithmic approaches.

Requirements

  • 4-5 years of experience in Data Science.
  • Expertise in time series algorithm development.
  • Proficiency in XGBoost, Pandas, and Scikit-learn.
  • Soft skills: curiosity, good development practices, ability to communicate complex ideas, and active listening.
  • Experience in retail is a plus.

Nice to Have

  • Familiarity with cloud platforms for deploying ML models.
  • Experience with big data technologies.

What We Offer

  • Full remote work with 2-3 seminars per year.
  • Attractive salary based on experience.
  • Impact-driven startup environment.
  • Senior team with a demanding and collaborative technical culture.
Why This Job8.2 of 10

This role offers a unique opportunity to work remotely as a Senior Machine Learning Engineer in a startup focused on sustainability in retail. The position promises a competitive salary and a collaborative environment.

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

About Mobiskill

Explore Mobiskill careers in 2026 and discover a range of exciting job openings, including remote, hybrid, and office roles. Utilize our advanced filters to tailor your search, track your applications, and gain valuable company insights. With a focus on your career growth, Mobiskill offers diverse opportunities that align with your skills and aspirations. Start your journey towards a fulfilling career today!

Industry
Tech
Location
Remote

Who Will Succeed Here

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Proficient in using XGBoost and scikit-learn for developing and optimizing machine learning models tailored for retail applications, demonstrating a strong ability to implement feature engineering techniques.

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Self-motivated and disciplined individual who excels in a remote work environment, able to manage time effectively while collaborating with cross-functional teams to deliver AI solutions.

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Analytical mindset with a strong focus on data analysis, capable of translating complex datasets into actionable insights that drive business decisions in a fast-paced retail context.

Learning Resources

→Machine Learning with XGBoostarticle
→Data Analysis with Pandascourse
→Feature Engineering for Machine Learningcourse

Career Path

Senior Machine Learning Engineer(Now)→Lead Machine Learning Engineer(1-2 years)→Machine Learning Director(3-5 years)

Market Overview

Market Size 2024
$22.6B
Annual Growth
38.8%
AI Adoption in Retail
75%
Investment in ML Solutions
+150%
Labour Demand for ML Engineers
+40%
Avg Salary for Senior ML Engineers
$130K

Skills & Requirements

Required
Machine LearningXGBoostPandas
Growing in Demand
Deep LearningNatural Language Processing (NLP)Cloud ML Services (AWS SageMaker, Azure ML)
Declining
Traditional Statistical MethodsRule-Based Systems

Domain Trends

Increased Personalization
Retailers are leveraging ML to enhance customer experiences, with 80% of companies investing in personalization technology.
Real-Time Analytics
Real-time data processing and analytics are becoming crucial, with 60% of retailers adopting ML for inventory management and demand forecasting.
Ethical AI and Transparency
As AI usage grows, 70% of retail organizations are focusing on ethical AI practices and transparency in their ML models.

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