ML Ops Engineer
1 miesiąc temu
This job is with Capco, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.
CAPCO POLAND
*We are looking for Poland based candidate. The job is remote but may require some business trips.
Joining Capco means joining an organisation that is committed to an inclusive working environment where you're encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It's important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table - so we'd love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
Capco Poland is a global technology and management consultancy specializing in driving digital transformation across the financial services industry. We are passionate about helping our clients succeed in an ever-changing industry.
We also are experts in focused on development, automation, innovation, and long-term projects in financial services. In Capco, you can code, write, create, and live at your maximum capabilities without getting dull, tired, or foggy.
As an ML Ops Engineer you will be responsible for developing, deploying and maintaining the infrastructure for Machine Learning to support Data Science and Machine Learning Teams. You will focus on automating modeling processes, monitoring models in production environments and managing the full ML lifecycle.
THINGS YOU WILL DO
Design and develop pipelines for training and deploying ML models
Automate and monitor ML processes, including version control and model updates
Collaborate with Data Science and Data Engineering teams to integrate ML models into production environments
Build and maintain systems for monitoring ML models to track performance and stability
Optimize cloud infrastructure (GCP) for ML deployments
Troubleshoot issues related to performance and availability of ML models in production
Ensure CI/CD best practices for ML models
TECH STACK: Python, TensorFlow, PyTorch, MLflow, Kubeflow, Airflow, CI/CD, GIT
Nice to have: Spark, Hadoop, GCP, Pub/Sub, Big Query, Kafka, Juniper, Apache NiFi, Hive, Impala, Cloudera,
SKILLS & EXPERIENCES YOU NEED TO GET THE JOB DONE
Experience with tools like: TensorFlow, PyTorch, MLflow, Kubeflow or similar
Experience managing data pipelines (Airflow)
Knowledge of DevOps practices (CI/CD, monitoring, automation)
Proficiency in Python (with ML libraries) and Git.
Experience with model monitoring solutions (e.g. Prometheus, Grafana).
Experience with Apache Spark, Hadoop or other big data tools is a huge plus
Great communication skills in English (both written and spoken)
Problem solver, team player with positive attitude :)
Experience in financial services will be also beneficial
University degree in computer science, mathematics, natural sciences, or similar field and relevant working experience
WHY JOIN CAPCO?
Employment contract and/or Business to Business - whichever you prefer
Possibility to work remotely
Speaking English on daily basis, mainly in contact with foreign stakeholders and peers
Multiple employee benefits packages (MyBenefit Cafeteria, private medical care, life-insurance)
Access to 3.000+ Business Courses Platform (Udemy)
Access to required IT equipment
Paid Referral Program
Participation in charity events e.g. Szlachetna Paczka
Ongoing learning opportunities to help you acquire new skills or deepen existing expertise
Being part of the core squad focused on the growth of the Polish business unit
A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients
A work culture focused on innovation and creating lasting value for our clients and employees
ONLINE RECRUITMENT PROCESS STEPS*
Screening call with the Recruiter
Technical interview: first stage
Client Interview
Feedback/Offer
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