Fullstack AI/ML Developer (office/remote)

HiQo Solutions; Kraków; Hybrid; PLN 60,000 - 80,000; Full time

Job summary

A technology company is seeking a versatile ML/AI Specialist to build end-to-end ML systems in Krakow or remotely. You will translate business problems into data-driven solutions, optimize ML models, and ensure system reliability. Ideal candidates have strong Python skills, MLOps experience, and knowledge of modern AI techniques. The role offers flexible working hours and excellent training opportunities.

Benefits

Flexible working time

Medical insurance

Internal education programs

Reward system for extracurricular activities

Qualifications

• 3-5+ years of experience building ML powered products.
• Strong Python and software engineering fundamentals.
• Proficiency with ML/DL stack and data modeling.

Responsibilities

• Translate business problems into ML/AI solutions.
• Build reliable data pipelines for training and inference.
• Monitor production systems and implement retraining.

Skills

Python

Machine Learning

Data Engineering

MLOps

Cloud Services

Containerization

SQL

Data Modeling

Deep Learning

API Development

Education

BS/MS in Computer Science or related field

Tools

scikit-learn

PyTorch

TensorFlow

Docker

AWS

Kubernetes

Airflow

Job description

Overview

We are seeking a versatile ML/AI Specialist who can translate business problems into data driven solutions and build end to end ML systems in partnership with our team. You will handle data exploration, modeling, deployment, and monitoring, owning the full lifecycle from concept to production. The ideal candidate combines solid software engineering and practical machine learning skills with hands on MLOps, cloud experience, and expertise in modern AI, including LLMs and generative models.

Location: Poland (office in Krakow or Wroclaw, or 100% remote)

Responsibilities

• Translate business problems into ML/AI solutions and measurable success criteria.
• Build reliable data pipelines (batch and streaming) for training and inference; implement data validation and quality checks.
• Develop, train, and evaluate models (classical ML and deep learning) with reproducible experiments.
• Design and ship production services (APIs, batch jobs, streaming consumers) with automated tests and observability.
• Establish and maintain MLOps foundations: versioning code/data/models, experiment tracking, model registry, CI/CD, and automated deployments.
• Monitor production systems (latency, throughput, cost, model performance, drift) and implement retraining and rollbacks.
• Apply modern AI techniques: LLM integrations, retrieval augmented generation, fine tuning and adapters, prompt design and evaluation, guardrails.
• Optimize cost and performance (profiling, batching, caching, quantization, GPU utilization) and ensure reliability.
• Collaborate with product, data, and engineering stakeholders; document designs and decisions.

Qualifications

• 3-5+ years building ML powered products with production ownership (data - model - deployment - monitoring).
• Strong Python and software engineering fundamentals: clean code, testing, logging, type hints, code reviews, modular design.
• Proficiency with ML/DL stack: scikit-learn; PyTorch or TensorFlow; pandas/NumPy; solid grasp of evaluation metrics and experiment design.
• SQL and data modeling; experience with warehouses/lakehouses (eg BigQuery/Snowflake/Redshift) and ETL/ELT tools.
• Orchestration and pipelines: Airflow/Prefect/Dagster or similar.
• Containers and deployment: Docker; basic Kubernetes or serverless; API frameworks (FastAPI/Flask).
• Cloud experience (AWS/GCP/Azure) including storage, compute, networking, and IAM basics.
• MLOps tooling: experiment tracking and model management (MLflow, Weights & Biases), model registry, artifact/version control.
• Monitoring/observability: metrics, tracing, and alerting (Prometheus/Grafana/CloudWatch/Datadog); model drift monitoring.
• Practical AI/LLM experience: using hosted APIs or open source models, embeddings/vector databases (FAISS/Pinecone/pgvector), RAG patterns, safety/guardrails.
• Clear communication and the ability to scope, estimate, and deliver incrementally.
• BS/MS in Computer Science, Data Science, Statistics, Engineering, or equivalent practical experience.
• English Proficiency - B2+

NICE TO HAVE

• Infrastructure as Code (Terraform/CloudFormation), Helm, KServe/SageMaker/Vertex AI/Azure ML.
• Streaming systems (Kafka/Kinesis/Pub/Sub) and real time inference.
• Feature stores, data contracts, and data governance.
• Performance tuning: ONNX/TensorRT, quantization, distillation, GPU scheduling; Numba/Cython.
• Security and compliance basics for ML systems, PII handling, secrets management.
• A/B testing, causal inference, and product analytics.

WE OFFER YOU

• Flexible working time - you can agree on it within the team
• Necessary tools and equipment
• Communication in English - for foreign customers and international teams
• Simple structure and open door style of communication
• Full time English teachers
• Medical insurance for employees
• HiQo University - internal education and training programs
• HIQO COINS - a system of rewarding employees for extracurricular activities