Expert in AI/ NLP/ ML

Sword Group

Belgium · Full-time · Mid-Senior

Job Description

The external service provider will be responsible for the following tasks:

Design, implement, and maintain a scalable, reliable, and secure hybrid cloud ML Ops infrastructure for deploying, testing, managing, and monitoring ML models in various environments.
Develop and maintain software applications in the areas of Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL), and/or Artificial Intelligence (AI).
Collaborate closely with data scientists and back-end developers to construct, test, integrate, and deploy ML models.
Analyze performance metrics, troubleshoot issues, and ensure high availability and reliability.
Design CI/CD pipelines, utilize orchestration solutions, and data versioning tools.
Create automated anomaly detection systems, continuously monitor performance, and optimize ML pipelines for scalability, efficiency, and cost-effectiveness.
Architect IT solutions in the NLP/ML/AI domains, considering master- and meta-data management concepts, and coordinate their implementation.
Provide security studies, security assessments, and guidance on information system projects.
Offer support and guidance to other team members on MLOps practices.

Knowledge and Skills Required:

Excellent knowledge of managing an on-prem and/or cloud MLOps infrastructure.
Excellent knowledge of containerization and orchestration platforms (e.g. Kubernetes, Docker, Podman, EKS, PKS).
Good knowledge of MLflow, TensorFlow (TFX) or equivalents.
Good knowledge of Airflow.
Good knowledge of AWS and/or Azure.
Good knowledge of Python.
Good knowledge of Unix and Bash.
Good knowledge agile software development methodologies.
Good knowledge of infrastructure as code (Terraform, CloudFormation).
Good knowledge of messaging services and platforms (e.g. Kafka, Redis, RabbitMQ).
Knowledge of data security measures (knowledge of encryption mechanisms and ML security is considered a plus).
Knowledge of NoSQL databases, such as Elasticsearch, MongoDB, Cassandra, HBase, etc.
Knowledge of query languages, such as SQL, Hive, Pig, etc. and with information extraction.
Experience with data analytics over big datasets, non-structured databases as well as data lakes.
Experience with monitoring and logging tools (e.g. ELK stack, Prometheus, Grafana, OpenTelemetry, Cloudwatch).
Experience with model testing and model validation in production environments.
Ability to write clear and structured technical documentation.
Excellent knowledge of on-prem or cloud solutions for data science applications.
Ability to give business and technical presentations.
Ability to apply high-quality standards.
Ability to cope with fast-changing technologies.
Very good communication skills with technical and non-technical audiences.
Analysis and problem-solving skills.
Capability to write clear and structured technical documents.
Ability to participate in technical meetings and good communication skills.

Optional Certifications:

AWS Certified Machine Learning.
Microsoft Azure AI Engineer Associate.

Key Skills

Ranked by relevance

cloud mlops natural language processing artificial intelligence infrastructure as code high availability containerization machine learning elasticsearch deep learning kubernetes prometheus tensorflow terraform cassandra grafana docker mlflow nosql redis kafka hbase unix cicd sql aws elk eks ai

Related Jobs

3 roles aligned with this opportunity

View all jobs