Data & Mlops Engineer (Ai Start-up)

**Helping people stay employable
**About JobTech**
JobTech is the world's leading artificial intelligence and big labour data analytics product company that empowers leaders to develop people for new work realities, driven by real labour market needs and individuals' personal aspirations. JobTech is growing rapidly with global big names customers from both private and public sectors.

**About the Team**
At JobTech, we are obsessed with improvements, inventing the future and empowering connections. Be surrounded by an enthusiastic team, excited to solve human capital business problems in talent development, using deep technology and labour market data. We embrace empowerment and love seeing what each individual member of the team brings to the table. We are hands-on dreamers, brought together with the common goal of helping people stay employable. If you've always known you were made for something greater, and would like to be a part of changing the HR tech-scape, we want you.

We are looking for someone who is excited to work in an AI start-up and is willing to develop him/herself in the HRTech space. This role would be ideal for someone who loves to deal with data and systems.

In this role, you’ll get to:

- Data Engineering:

- Build and manage extract, transform, and load pipelines efficiently and reliably for analytical and machine learning purposes
- Design and implement reliable, scalable and robust data systems that support core products and business
- Implement and automate data quality checks, data validation processes, and error handling mechanisms to ensure the reliability and consistency of the data.
- Implement and maintain data governance practices, ensuring compliance with relevant data privacy and security regulations.
- Maintain cloud-based data infrastructure on platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure as well as on on-premise servers.
- MLOps:

- Develop and implement machine learning operations (MLOps) processes, including model deployment, monitoring, and version control.
- Work closely with data scientists to deploy, monitor, and optimize machine learning models in production.
- Collaborate with DevOps teams to design and implement scalable, reliable, and automated machine learning deployment and management processes.
- Collaborate with data analytics and software engineering teams to ensure that models and algorithms are integrated with the project’s overall architecture.
- Stay up to date with the latest advancements in data engineering, cloud technologies, and MLOps, and proactively recommend and implement improvements to our data and machine learning infrastructure.

So here’s what we’re looking for:

- Proven experience as a Data Engineer, MLOps Engineer, or similar roles, with a good understanding of data engineering concepts, ETL processes, data warehousing and data lakes.
- Excellent programming skills in Python or Java, with experience implementing data and machine learning pipelines.
- Strong SQL and NoSQL skills. Expertise in working with relational and NoSQL databases.
- Experience with cloud-based data platforms such as AWS, GCP, or Azure, including services like S3, Redshift, BigQuery, or Azure Data Lake.
- Proficiency with workflow tools such as Airflow
- Understanding of big data technologies.
- Knowledge of data modeling techniques, data governance principles, and best practices in MLOps.
- Experience with containerization and orchestration tools like Docker and Kubernetes.
- Basic familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Resourceful to plug knowledge gaps when necessary.
- Passionate about machine learning and data-driven intelligence systems.
- Excellent communication and interpersonal skills.
- Team player, self-starter, ability to work on multiple projects.