Machine Learning Threat Intelligence Engineer

OpenKyber LLC
17 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

Java
Agile Methodologies
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Azure
C Sharp (Programming Language)
Cloud Computing
Computer Programming
Continuous Integration
DevOps
Github
Python
Machine Learning
Systems Development Life Cycle
TensorFlow
Prometheus
Software Engineering
Data Streaming
Systems Integration
Data Logging
Large Language Models
Grafana
Prompt Engineering
Generative AI
Cyber Threat Analysis
GIT
Cloudformation
Containerization
Kubernetes
Kafka
Machine Learning Operations
REST
Terraform
Data Pipelines
Docker
ELK
Jenkins
Go
Programming Languages
Microservices

Job description

We are seeking a highly motivated AI Engineer with a strong background in software engineering and hands-on experience in applied AI/ML to support AI Transformation initiatives. The ideal candidate will have 1-3 years of experience building, integrating, or deploying AI-driven solutions and be proficient in at least one modern programming language (GO, Python, Java, C#) and exposure to DevOps practices & Cloud environment. You will work closely with cross functional teams to design, develop, and operationalize AI solutions that enhance automation, improve decision-making, and drive business value.

Requirements

  • 1-3 years of experience in AI/ML engineering or related roles
  • Strong programming skills in one or more programming languages: GO/Java/Python/C#
  • Good understanding of machine learning concepts and lifecycle
  • Hands-on experience with ML frameworks/libraries
  • Exposure to DevOps practices (CI/CD, automation, environment management)
  • Experience with tools like Git, Jenkins, GitHub Actions, or similar
  • Familiarity with containerization (Docker) and basics of orchestration (Kubernetes)
  • Understanding of REST APIs and microservices architecture
  • Exposure to cloud platforms (AWS, Azure)
  • Good understanding of SDLC process
  • Experience working in Agile environments
  • Strong analytical and problem-solving abilities
  • Good communication and stakeholder collaboration skills
  • Ability to work in fast-paced, evolving environments
  • Continuous learning mindset, * Experience with MLOps tools/platforms
  • Exposure to Generative AI / LLMs (prompt engineering, embeddings, fine-tuning)
  • Familiarity with infrastructure as code (Terraform, CloudFormation)
  • Experience with monitoring/logging tools (Prometheus, Grafana, ELK stack)
  • Knowledge of data pipelines and streaming tools (Kafka, Airflow)

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