Machine Learning Engineer
⚲ Warszawa
23 520 - 26 880 PLN netto (B2B)
Wymagania
- Python
- Machine Learning
- Docker
- Kubernetes
- Microsoft Azure Cloud
- Apache Airflow
- MLOps
- Apache Kafka
- Apache Spark
Opis stanowiska
In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking an experienced a Machine Learning Engineer, who will be responsible for guiding the successful development, automation and governance of AI/ML Solutions to the internal customers. The MLE will be responsible for collaborating with Data Scientists, Domain Experts and Product Owners to build and deploy the end-to-end AI Products for the company. The role will require working knowledge of Cloud, DevOps/ MLOps, Machine Learning, Deep Learning and Application Development. This position will also be involved in the formulation of key business requirements to be solved and rationalizing the various best practices to solve those problems.
Project information:
• Type of project: IT Services
• Office location: Warsaw
• Budget: 140 – 160 PLN net/h on b2b
• Work model: Hybrid (2 days/week in the office)
• Project length: Long-term
• Only candidates with citizenship in the European Union and residence in Poland
• Start date: ASAP (depending on candidate’s availability)
Project scope:
• Script production-ready codes
• Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads
• Architect, automate and orchestrate Dev-Ops/ ML-Ops pipelines on cloud
• Craft re-usable tools and frameworks to monitor, optimize and maintain ML solutions
• Design and implement data engineering pipelines (ETL)
• Understand business problems and collaborate within the team to ensure scalability, business continuity and appropriate turnaround time
• Conduct internal workshops and external meetups, participate in external conferences, and give talks
• Continuously evolve your craft by keeping up to date with the new developments in AI/ML and related technologies and upskilling on these as needed
• Collaborate with Data Scientists, Domain Experts, and Product Owners to build and deploy the end-to-end AI Products
Competence demands:
• A bachelor's or master’s degree in Computer Science, Operations Research, Mathematics, and Computing with 3-4 years of relevant experience
• Experience in working with large data sets, coming from varied sources
• Excellent Programming Skills in Python
• Experience with containerization (Docker) and container orchestration using Kubernetes
• Experience in Cloud Application Development (Google Cloud Platform & Azure Preferred)
• Great at solving problems, debugging, troubleshooting, and designing & implementing solutions to complex technical issues
• Experience designing, building, and maintaining ETL workflows and data pipelines, using orchestration tools like Apache Airflow, Kubeflow, or similar
• Proficiency with DevOps practices, including CI/CD, Git-based workflows
• Comfortable working in Unix/Linux environments
• Hands on experience of designing, building, and supporting RESTful APIs
• Working knowledge of machine learning and deep learning concepts, and experience supporting model deployment and monitoring
• Very good English skills
Nice to have:
• Understanding of Deep learning platforms such as Keras, TensorFlow, and/or PyTorch
• Understanding of key Machine Learning & Deep Learning Algorithms
• Knowledge of Oilfield terminology and business practices
• Experience with IoT/ Edge technology
• Recognized open-source contributions
• Familiarity with data engineering tools (Flink/Spark/Kafka etc.)
• Experience with big data stack (Spark, Hadoop, Storm, Hive & Pig) and NoSQL stores
We offer:
• Hybrid working model (2 days/week in the office in Warsaw)
• Collaboration with senior engineers and cross-functional AI teams
• Dynamic and innovation-driven engineering environment
• Full-time job agreement based on b2b
• Private medical care with dental care (covering 70% of costs)
• Multisport card (also for an accompanying person)
• Life insurance
Project information:
• Type of project: IT Services
• Office location: Warsaw
• Budget: 140 – 160 PLN net/h on b2b
• Work model: Hybrid (2 days/week in the office)
• Project length: Long-term
• Only candidates with citizenship in the European Union and residence in Poland
• Start date: ASAP (depending on candidate’s availability)
Project scope:
• Script production-ready codes
• Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads
• Architect, automate and orchestrate Dev-Ops/ ML-Ops pipelines on cloud
• Craft re-usable tools and frameworks to monitor, optimize and maintain ML solutions
• Design and implement data engineering pipelines (ETL)
• Understand business problems and collaborate within the team to ensure scalability, business continuity and appropriate turnaround time
• Conduct internal workshops and external meetups, participate in external conferences, and give talks
• Continuously evolve your craft by keeping up to date with the new developments in AI/ML and related technologies and upskilling on these as needed
• Collaborate with Data Scientists, Domain Experts, and Product Owners to build and deploy the end-to-end AI Products
Competence demands:
• A bachelor's or master’s degree in Computer Science, Operations Research, Mathematics, and Computing with 3-4 years of relevant experience
• Experience in working with large data sets, coming from varied sources
• Excellent Programming Skills in Python
• Experience with containerization (Docker) and container orchestration using Kubernetes
• Experience in Cloud Application Development (Google Cloud Platform & Azure Preferred)
• Great at solving problems, debugging, troubleshooting, and designing & implementing solutions to complex technical issues
• Experience designing, building, and maintaining ETL workflows and data pipelines, using orchestration tools like Apache Airflow, Kubeflow, or similar
• Proficiency with DevOps practices, including CI/CD, Git-based workflows
• Comfortable working in Unix/Linux environments
• Hands on experience of designing, building, and supporting RESTful APIs
• Working knowledge of machine learning and deep learning concepts, and experience supporting model deployment and monitoring
• Very good English skills
Nice to have:
• Understanding of Deep learning platforms such as Keras, TensorFlow, and/or PyTorch
• Understanding of key Machine Learning & Deep Learning Algorithms
• Knowledge of Oilfield terminology and business practices
• Experience with IoT/ Edge technology
• Recognized open-source contributions
• Familiarity with data engineering tools (Flink/Spark/Kafka etc.)
• Experience with big data stack (Spark, Hadoop, Storm, Hive & Pig) and NoSQL stores
We offer:
• Hybrid working model (2 days/week in the office in Warsaw)
• Collaboration with senior engineers and cross-functional AI teams
• Dynamic and innovation-driven engineering environment
• Full-time job agreement based on b2b
• Private medical care with dental care (covering 70% of costs)
• Multisport card (also for an accompanying person)
• Life insurance
🔍 Dekoder Ogłoszenia
🔴
guiding the successful development, automation and governance of AI/ML Solutions to the internal customers
Może oznaczać odpowiedzialność za procesy i strategię, a niekoniecznie bezpośrednie kodowanie i implementację.
🔴
collaborating with Data Scientists, Domain Experts and Product Owners to build and deploy the end-to-end AI Products for the company
Rola może wymagać dużo pracy zespołowej i komunikacji, potencjalnie kosztem samodzielnego, głębokiego technicznego zaangażowania.
🔴
working knowledge of Cloud, DevOps/ MLOps, Machine Learning, Deep Learning and Application Development
Zakres wymaganych umiejętności jest bardzo szeroki i może sugerować, że będziesz musiał zajmować się wieloma różnymi obszarami, a nie tylko ML.
🔴
involved in the formulation of key business requirements to be solved and rationalizing the various best practices to solve those problems
Może oznaczać, że będziesz musiał spędzać dużo czasu na analizie biznesowej i definiowaniu problemów, zanim przejdziesz do technicznych rozwiązań.
🔴
Script production-ready codes
Choć brzmi technicznie, może oznaczać bardziej tworzenie skryptów automatyzujących niż budowanie złożonych, skalowalnych systemów ML od podstaw.