AI/ML Engineer

Support your team in key Data & AI initiatives

Artificial Intelligence and Machine Learning are becoming integral components of modern analytical, operational, and decision-making systems. Successful implementation requires solid engineering, experience, and well-designed architecture.

Our AI/ML engineers support clients in designing, building, and maintaining scalable data and model-driven systems—from data engineering and pipeline automation to deployment and monitoring of models in production environments.

We provide both individual specialists and complete teams, experienced in working across cloud (Azure, AWS, GCP) and hybrid environments.

Selected areas where we support our clients:

Migration to modern data and AI platforms (e.g., Databricks)
Design and automation of data pipelines—from raw data to decision models
Integration of AI/ML components with existing analytical and operational applications
Deployment and lifecycle management of predictive and generative models
Automation of model deployment and monitoring (MLOps)
Model evaluation using industry-standard frameworks

What you gain by working with us:

Faster execution

eliminate long recruitment and onboarding cycles
Flexible engagement

we provide individual engineers or full, ready-to-deploy teams
End-to-end capabilities

from specialized pilots to full-scale enterprise-grade cloud or on-premise solutions
Cost optimization

we focus on both delivery and long-term operational efficiency
Risk reduction

leverage our experience to de-risk key decisions and AI/ML deployments

The expertise you need

Modern AI/ML systems must be functional, scalable, secure, and cost-effective. Our engineers have experience designing and implementing AI/ML solutions that meet these requirements—across technologies and domains.

We offer experts in:

AI/ML integration across cloud platforms (Azure, GCP, AWS)
Integration of language models (OpenAI, Gemini, Anthropic)
DataOps, MLOps, AIOps, DevOps

Technologies & Capabilities

Our engineers work with:

Public clouds: Azure, AWS, GCP
AI/ML platforms and frameworks: MLflow, Airflow, Kubeflow, Databricks, Apache Spark, Iceberg, Kafka, HuggingFace, TensorFlow, PyTorch
Programming languages: Python, Java, Scala, C++
CI/CD & DevOps tools: Jenkins, GitLab CI, GitHub Actions

Our Certifications

AWS Certified Solutions Architect
Azure Solutions Architect Expert
Azure Data Engineer Associate (DP-203)
GCP Cloud Developer
Google Professional Cloud Architect
Databricks Certified Associate Developer for Apache Spark 3.0

Why Craftware?

Proven expertise:

We deliver AI/ML components integrated with large-scale big data environments at enterprise level
Databricks partner

We leverage both native and open-source AI/ML technologies
Cost and performance focus

We help clients achieve the right balance between capability, scalability, and efficiency