AI/Ml Engineer

AI/ML Engineer

(B2B / Remote Work / Long-Term Cooperation)

About Us

We are Square One. For 30 years, we’ve specialized in IT recruitment, and we know exactly what IT experts like you need. If you’re looking for new challenges, aren’t afraid of skill-building projects, and want to stay on the technological cutting edge—then you’ve come to the right place!

About the Project

Our client from the pharmacy sector is seeking a AI/ML Engineer to join their team and have a real impact on product and company development from day one.We need a highly skilled AI/ML Engineer to help us build AI-powered applications from start to finish. We'll be working on AI and GenAI solutions, taking them from concept to production and beyond.

If you want to work with an experienced team and thrive in an environment where your ideas and initiative are highly valued, this role is for you!

Your Responsibilities

1. Generative AI Application Development: Work with developers and stakeholders in Agile teams to integrate LLMs and classical AI techniques into user-friendly applications that perform well in real time.
2. Algorithm Development: Create, customize, optimize, and fine-tune LLM-based and other AI algorithms for tasks like text generation, summarization, information extraction, chatbots, AI agents, code generation, document analysis, sentiment analysis, and data analysis.
3. LLM Fine-Tuning and Customization: Adjust pre-trained LLMs to meet specific business needs using techniques like prompt engineering, transfer learning, and few-shot learning to improve model performance.
4. End-to-End Pipeline Development: Build and maintain complete ML pipelines, including data ingestion, preprocessing, training, evaluation, deployment, and monitoring. Use MLOps best practices to make the workflows scalable and efficient.
5. Performance Optimization: Improve model inference speed, reduce latency, and manage resource usage across cloud services and GPU/TPU architectures.
6. Scalable Model Deployment: Work with other developers to deploy models at scale using cloud infrastructure (AWS, Azure) while ensuring high availability and fault tolerance.
7. Monitoring and Maintenance: Continuously monitor and refine deployed models, using feedback loops and incremental fine-tuning to maintain accuracy and reliability. Address drifts and biases as they arise.
8. Software Development: Follow software development best practices, including writing unit tests, configuring CI/CD pipelines, containerizing applications, prompt engineering, and setting up APIs. Ensure robust logging, experiment tracking, and model monitoring.

What We’re Looking For 

1. Experience: 3+ years in AI/ML engineering with exposure to both classical machine learning methods and language model-based applications.
2. Technical Skills: Advanced proficiency in Python and experience with deep learning frameworks like PyTorch or TensorFlow. Expertise with Transformer architectures, hands-on experience with LangChain or similar LLM frameworks, and experience designing end-to-end RAG systems using state-of-the-art orchestration frameworks.
3. MLOps Knowledge: Strong understanding of MLOps tools and practices, including version control, CI/CD pipelines, containerization, orchestration, Infrastructure as Code, and automated deployment.
4. Deployment: Experience deploying LLM and other AI models with cloud platforms (AWS, Azure) and machine learning workbenches for robust and scalable productization.
5. Practical Overview: Experience with AWS services for designing cloud solutions. Familiarity with Azure is a plus. Experience with GenAI-specific services like Azure OpenAI, Amazon Bedrock, Amazon SageMaker JumpStart, etc.
6. Data Engineering: Expertise in working with both structured and unstructured data, including data cleaning and feature engineering with data stores like vector, relational, NoSQL databases, and data lakes through APIs.
7. Model Evaluation and Metrics: Proficiency in evaluating both classical ML models and LLMs using relevant metrics.
8. Optimization Techniques: Experience optimizing models for performance.
9. Problem-Solving Skills: Strong analytical skills to tackle complex engineering challenges, integrate new technologies, and improve existing processes.

What We Offer

• Remote/
• B2B Contract – flexible collaboration, straightforward settlements.
• Long-Term Cooperation – we offer long-lasting projects, and once they end, we strive to find new ones that suit your skill set.
• Fast and clear recruitment process - only one stage with the end client