Sword Group

AI/NLP/ML Expert

Sword Group

full-time

Posted on:

Location Type: Remote

Location: Belgium

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Tech Stack

AirflowAWSAzureCassandraCloudDockerElasticSearchGrafanaHBaseKafkaKubernetesMongoDBNoSQLPrometheusPythonRabbitMQRedisSQLTensorflowTerraformUnix

About the role

  • 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

Requirements

  • 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
Benefits
  • 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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Natural Language ProcessingMachine LearningDeep LearningArtificial IntelligencePythonUnixBashTerraformCloudFormationSQL
Soft Skills
communication skillsanalysis skillsproblem-solving skillstechnical documentationpresentation skillsability to cope with fast-changing technologiescollaborationguidancesupporthigh-quality standards