AI/ML Engineer at Punch Digital Agency
Lagos, , Nigeria -
Full Time


Start Date

Immediate

Expiry Date

31 Aug, 25

Salary

0.0

Posted On

01 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Databases, Data Structures, Zeromq, Statistics, Processing, Data Modeling, Git, Sql, Probability, Github, Algorithms, Keras, Software Architecture, Docker, Mongodb

Industry

Information Technology/IT

Description

ABOUT PUNCH:

Punch is a full-service digital agency dedicated to creating exceptional digital experiences. We are expanding our team in Lagos and seeking experienced AI/ML Developers to join us. If you are passionate about innovation and thrive in dynamic environments, we want to hear from you.

TECHNICAL SKILLS:

  • Experience developing applications on Linux environments.
  • Proficiency with DevOps tools: Docker, Git (GitLab, GitHub), and CI/CD pipelines.
  • Familiarity with modern Computer Vision techniques.
  • Understanding of high-performance computing and parallel processing.
  • Knowledge of network/messaging protocols (UDP, ZeroMQ, RESTful API).
  • Experience interfacing with databases (SQL, MongoDB, etc.).
  • Strong command of ML frameworks (Keras, PyTorch) and libraries (scikit-learn).

PROGRAMMING SKILLS:

  • Deep understanding of data structures, data modeling, and software architecture.

ANALYTICAL SKILLS:

  • Strong background in math, probability, statistics, and algorithms.
  • Proven ability to perform statistical analysis and interpret AI/ML test results.

PROFESSIONAL EXPERIENCE:

  • Proven track record as a Machine Learning/AI Engineer or in a similar role.
  • Experience building and deploying ML applications in real-world scenarios.
Responsibilities
  • Study and transform data science prototypes into scalable solutions.
  • Design and develop machine learning systems and applications based on requirements.
  • Research, implement, and optimize AI/ML algorithms and tools.
  • Select appropriate datasets and data representation techniques.
  • Run AI tests and experiments, analyze results, and fine-tune models as needed.
  • Train, retrain, and improve machine learning systems when necessary.
  • Extend existing machine learning libraries and frameworks to enhance capabilities.
  • Conduct statistical analysis to validate and refine AI/ML models.
  • Stay updated with the latest trends and advancements in AI/ML.
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