LLM – Python for Machine Learning Engineer (Remote) at Gramian Consulting Group

Group Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

We are recruiting to fill the position below:

Job Title: LLM – Python for Machine Learning Engineer

Location: Nigeria
Commitments Required : 40 hours per week with 4 hours of overlap with PST
Start date: As soon as possible
Duration: The project will last five weeks

Role Overview

• We are seeking skilled and experienced ML Developers to join our innovative team.
• The ideal candidate will have strong hands-on ML experience with the ability to understand complex data models and translate business requirements into efficient solutions that capture business context accurately.
• Participation in machine learning competitions is a strong plus.

Responsibilities
What does day-to-day look like?

• Develop and maintain ML solutions, including data pipelines, model training, evaluation, and optimization.
• Collaborate with business stakeholders to gather and clarify requirements
• Translate business requirements into ML code that accurately reflects business logic
• Write efficient, maintainable, and well-documented ML solutions
• Participate in code reviews and follow established development standards
• Effectively analyze and select the best algorithms, optimize ML solutions for performance improvement and accuracy
• Create and maintain technical documentation for developed solutions
• Support testing activities and resolve data-related issues

Requirements

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
• 4+ years of hands-on ML development experience
• Proficiency in at least some of the ML areas and frameworks, including:
  • Supervised learning (classification, regression, …)
  • Unsupervised learning (clustering, anomaly detection, …)
  • Time-series analysis
  • Natural Language Processing (NLP)
  • Computer Vision (CV)
  • Statistical modeling
• Ability to understand and apply different models to real-world use cases
• Hands-on experience with DS and ML solutions in production environments
• Strong understanding of data cleaning and wrangling, feature engineering, model optimization, and evaluation metrics
• Proficiency in Python and its common data science libraries (e.g., Pandas, NumPy, Scikit-learn)
• Bonus: Experience and knowledge in Kaggle competitions and Benchmarks, such as MLEBench.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online

Interview Process: Two rounds of interviews (60 min technical + 30 min technical & cultural discussion)