Apply for job
View Job
We are the 1st Hub for Developers! Our motto is “From Developers to Developers”! Our vision is to provide real career opportunities for candidates that want to take the next step in their career. Code.Career is the first process that you will speak with developers (only!) and tech (freak) experts!
Position Overview
Our Client is seeking an experienced AI Engineer to join their growing AI team. You will be responsible for designing, building, and maintaining end-to-end artificial intelligence solutions that move from prototype to production, working with cutting-edge LLM technologies and modern AI frameworks.
Key Responsibilities
AI Development & Implementation
- Design and develop production-ready AI/ML systems and applications
- Implement and fine-tune Large Language Models (LLMs) using frameworks like LangChain, OpenAI APIs, and Hugging Face
- Build and optimize prompt/context engineering solutions and Retrieval-Augmented Generation (RAG) pipelines
- Develop vector store embeddings and semantic search capabilities
- Create multi-model orchestration workflows for complex AI applications
Data & Model Management
- Gather, preprocess, and manage large-scale datasets for model training
- Develop and maintain machine learning models using TensorFlow, PyTorch, or similar frameworks
- Implement model evaluation, monitoring, and observability mechanisms
- Perform model versioning and lifecycle management using MLflow or similar tools
Deployment & Operations
- Deploy AI models to production using cloud platforms (AWS, Azure, or GCP)
- Containerize applications using Docker and manage infrastructure with Kubernetes
- Build and maintain RESTful APIs for model integration
- Implement CI/CD pipelines for automated model deployment
- Monitor model performance, drift, and system health in production
Collaboration & Innovation
- Work cross-functionally with product managers, data scientists, and DevOps teams
- Translate business requirements into technical AI solutions
- Stay current with emerging AI technologies and best practices
- Document architecture, processes, and technical decisions
Required Qualifications
Education
- Bachelor’s degree in Computer Science, Engineering, Machine Learning, or related quantitative field
- Master’s degree preferred
Experience
- 3+ years of hands-on experience putting Machine Learning models into production
- Proven track record of developing and deploying AI/ML systems at scale
- Experience with end-to-end ML lifecycle from data preparation to production deployment
Technical Skills
- Programming: Expert-level proficiency in Python (required); Java or C++ is a plus
- ML Frameworks: Deep expertise in TensorFlow and/or PyTorch
- LLM Tools: Hands-on experience with LangChain, OpenAI APIs, or similar LLM frameworks
- MLOps: Experience with MLflow, model versioning, and lifecycle management
- Cloud Platforms: Proficiency with AWS SageMaker, Azure ML, or Google AI Platform
- Containerization: Strong experience with Docker for creating reproducible environments
- Orchestration: Knowledge of Kubernetes for scalable deployments
- APIs: Experience developing and integrating RESTful APIs
- Databases: Familiarity with both SQL and NoSQL databases
Core Competencies
- Strong mathematical foundations (linear algebra, statistics, probability)
- Deep understanding of machine learning algorithms and neural networks
- Knowledge of distributed computing and scalable system design
- Understanding of AI ethics, bias mitigation, and responsible AI practices
- Excellent problem-solving and analytical skills
- Strong communication skills for technical and non-technical audiences
Preferred Qualifications
- Experience with Generative AI and prompt engineering techniques
- Knowledge of vector databases (Pinecone, Weaviate, Chroma)
- Familiarity with NLP, computer vision, or reinforcement learning
- Experience with A/B testing and experimentation frameworks
- Contributions to open-source AI/ML projects
- Publications or research in AI/ML domains
- Experience with real-time inference and low-latency systems
What They Offer
- Competitive salary and equity package
- Comprehensive health benefits
- Professional development and learning opportunities
- Flexible work arrangements (remote/hybrid options)
- Cutting-edge AI technology stack
- Collaborative and innovative team environment
- Opportunity to work on impactful AI projects
Manage Consent
Functional Always active
We use cookies to ensure the proper functionality of our website, enhance your browsing experience, and provide personalized content. Functional cookies are essential for enabling basic features such as page navigation, secure access to areas of the site, and remembering your preferences. Without these cookies, our website cannot perform optimally.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.
The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
