Job Openings ML Engineering Lead

About the job ML Engineering Lead

About TEKEVER:

At TEKEVER, we are at the forefront of leveraging cutting-edge data and AI technologies to drive innovation and deliver exceptional value to our clients. Our team is passionate about creating intelligent solutions that transform countries, governments, businesses and improve lives.

TEKEVERs mission is to provide our customers with actionable intelligence to make the best decisions faster - both in real-time and non-real-time - in the most challenging environments across the globe. We design and build state-of-the-art autonomous Unmanned Aerial Systems (UAS), both in terms of hardware and software platforms and are growing fast in multiple areas, within both Defense and Civil domains. Typical Use Cases that our portfolio of drones and AI platforms focus on are, amongst others, military surveillance & intelligence gathering, oil pipeline inspections, maritime surveillance, wildfire monitoring, crowd control, change detection, automated area search, sense & avoid, precision landing, swarming - and many more.

As such, we are significantly expanding our Data & AI function and are seeking a highly skilled and experienced ML Engineering Lead to guide our machine learning engineering team and contribute to our mission of excellence.

Job Overview:


As the ML Engineering Lead, you will be responsible for leading a team of machine learning engineers in the design, development, deployment and maintenance of machine learning models and systems. You will work closely with data scientists, software engineers and other stakeholders to ensure the successful implementation and integration of ML solutions. The ideal candidate will have a strong background in machine learning, software engineering and team leadership.

What will be your responsibilities:

  • Team Leadership: Lead, mentor and develop a team of machine learning engineers, fostering a collaborative and innovative work environment.

  • Project Management: Oversee the end-to-end lifecycle of machine learning projects, from concept to deployment, ensuring timely delivery and high-quality outcomes.

  • Model Development: Collaborate with data scientists to design and implement robust and scalable machine learning models and algorithms.

  • System Architecture: Define and implement the architecture for ML systems, ensuring they are scalable, reliable and efficient.

  • Deployment: Oversee the deployment of machine learning models into production environments, ensuring seamless integration and performance.

  • MLOps: Develop and maintain ML operations processes, including CI/CD pipelines, monitoring and automated retraining systems.

  • Performance Optimization: Optimize ML models and systems for performance, efficiency and scalability.

  • Collaboration: Work closely with cross-functional teams, including data science, software development, product management and IT, to define requirements and deliver solutions that meet business and technical needs.

  • Innovation: Stay current with the latest advancements in machine learning and AI technologies and drive the adoption of best practices and new techniques within the team.

  • Documentation: Ensure comprehensive documentation of models, algorithms, processes and systems for future reference and reproducibility.

Profile and requirements:

  • Education: Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.

  • Experience: 5+ years of experience in machine learning, software engineering, or a related field, with specific experience in leading teams and managing projects.

  • Technical Skills:

    • Strong programming skills in Python, as well as Go, Rust, R, Java or a similar language.

    • Strong proficiency in machine learning and deep learning frameworks such as TensorFlow, TensorRT, PyTorch, or scikit-learn.

    • Strong knowledge of ML model development, training and deployment processes.

    • Knowledge of software development best practices and tooling, including DevOps, version control (e.g., Git), continuous integration/continuous deployment (CI/CD), telemetry and monitoring, containerization (Docker, Kubernetes) and infrastructure as code (IaC).

    • Familiarity with relevant tooling such as ClearML for ML lifecycle management.

    • Experience with experimentation platforms such as Jupyter Notebooks.

    • Knowledge of data engineering concepts and tools for data preprocessing and ETL.

    • Experience in getting machine learning products to production.

    • Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud), with a focus on Google Cloud.

  • Analytical Skills: Excellent analytical and problem-solving skills with the ability to design innovative solutions to complex problems.

  • Communication: Strong verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders.

  • Attention to Detail: High attention to detail and a commitment to ensuring the accuracy and quality of work.

  • Adaptability: Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.

What we have to offer you:

  • An excellent work environment and an opportunity to create a real impact in the world;

  • A truly high-tech, state-of-the-art engineering company with flat structure and no politics;

  • Working with the very latest technologies in Data & AI, including Edge AI, Swarming - both within our software platforms and within our embedded on-board systems;

  • Flexible work arrangements;

  • Professional development opportunities;

  • Collaborative and inclusive work environment;

  • Salary compatible with the level of proven experience.

TEKEVER is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

If the above excites you, apply now! Send your CV to jobs@tekever.com.



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