Machine Learning Engineer - Deep Learning & Large Language Models (MLOps) at Uniccon Group

Uniccon Group is the home of innovative and customizable tech products to meet your needs. We combine world-class expertise, experience, and modern tools to scale up your productivity. Valuing and collaborating for the best services have kept us ahead of the market. Individuals, SMEs, organisation, and government agencies achieve more with us.

Uniccon Group owns Africa’s leading hub for STEM research, training, and solutions (STEMFocus). Research is the bedrock of our innovative services in the marketplace, payment gateway, workflow optimization, financial intel, cybersecurity, cloud infrastructure, and e-learning products. We are futuristic and leading with METAVERSE and NFTs in Africa. The operations extend to Agro-commodities processing and export, fashion brands, and general contracting business. It oversees operations across Africa, Asia, Europe, the Americas, and other parts of the world. The products are innovative, and customizable to meet market needs. Unicorn Group is a key player in their respective industries.

We are recruiting to fill the position below:

Job Title: Machine Learning Engineer - Deep Learning & Large Language Models (MLOps)

Location: Abuja
Job Schedule: Full-time

Job Description

• We are looking for a skilled Machine Learning Engineer with a strong background in deep learning and large language models (LLMs), particularly with experience in deploying and managing models using MLOps best practices.
• The ideal candidate will have hands-on experience with Hugging Face Transformers, Docker, PyTorch, and Python, along with a deep understanding of Machine Learning and LLMs.
• This role offers the opportunity to work on exciting projects that push the boundaries of AI and drive innovation.

Responsibilities

• Develop and deploy deep learning models, with a focus on large language models, using PyTorch and Hugging Face Transformers.
• Update and Utilize currently existing Deployment architecture for efficient and scalable deep learning Inferencing.
• Collaborate with cross-functional teams to understand project requirements and design scalable solutions that leverage LLMs.
• Implement MLOps best practices for model deployment, monitoring, and management, ensuring reliability and scalability.
• Optimize and fine-tune models for performance and efficiency, considering factors such as speed, accuracy, and resource utilization.
• Conduct research to stay updated on the latest advancements in deep learning, LLMs, and MLOps, and incorporate best practices into our workflows.
• Work closely with data engineers to ensure seamless integration of data pipelines with model deployment processes.
• Develop automated testing and evaluation frameworks to assess model performance and identify areas for improvement.

Qualifications and Skills

• Bachelor's or Master's Degree in Computer Science, Engineering, Mathematics, or a related field.
• Proven experience in developing and deploying deep learning models, with a focus on large language models.
• Strong proficiency in PyTorch,Mlflow, Docker, Kubernetes, Hugging Face Transformers, and Python. Experience with MLOps best practices and tools for model deployment and management.
• In-depth understanding of parallel programming and distributed deep learning training.
• Deep understanding of large language models and their applications across various domains.
• Solid understanding of machine learning concepts and algorithms. Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Application Closing Date
Not Specified.

Method of Application
Interested and qualified candidates should forward their CV to: [email protected] using the Job Title as the subject of the email.