Machine Learning Engineer
Remote job
Adarga is a rapidly scaling organisation and we are growing our technology department. As a Machine Learning (ML) engineer within the product team, you will bring your expertise to a full stack technology team working to solve Natural Language Processing (NLP) linguistic challenges. Adarga is product focussed and is developing the world’s leading AI software to provide effortless access to knowledge from real world data and enable our customers to make better decisions.
We are looking for an experienced ML engineer with a focus on deploying deep learning models to a production cloud environment and a strong computer science background. You will be hands-on with day-to-day project work focussed on deploying technical solutions to deliver a roadmap which is aligned to core product features. You will also work alongside a product manager to develop new features.
The ML engineer will be responsible within the product team to implement Adarga’s ML Ops strategy. This is a strategic initiative to ensure, repeatability, explainability and operational efficiency are ingrained in our AI software.
As the ML Engineer, you will report to the product tech lead and data science manager.
Requirements
Essential skills
- Experience of establishing and managing ML flow / pipelines
- Experience deploying Data Science solutions in a commercial environment and the ability to quantify model deployment success criteria
- Excellent awareness of software engineering and coding best practices
- Experience of establishing and managing ML flow / pipelines
- Experience building and deploying solutions to the Cloud
- ML Ops research is advancing at a rapid pace, an enthusiasm for continual learning is required to maintain your expertise
- Excellent communication skills and awareness of project management techniques, capable of operating within a team of 6-7 people to influence and develop best practice
- Ability to thrive effectively in predominantly remote working environment
- MSc or equivalent professional experience in a ML/Data Engineering/Computer Science role
Nice to have skills
- Experience of modern NLP techniques is an advantage
- Experience of using data science platforms and frameworks, for data tagging, model training and benchmarking
- An experimentation mindset to solve business problems
- Knowledge of AI techniques, including how to train, fine tune and apply deep learning models
- Experience of some of the following technologies (or equivalent) would be beneficial, Python, Seldon, Helm, Pachyderm, AWS or other cloud technologies, Kubernetes, Docker, Knowledge graphs, Graph databases, SQL and Relational databases.
Further information
At Adarga we use Kanban principles and daily stand-ups to track work tasks and it will be your responsibility to attend these and document your work to ensure it is repeatable. It will be necessary to take part in cross functional and cross team communication to enhance collaboration, these will take the form of knowledge shares, reading groups, chapter group meetings, workshops and innovation projects.
You will be set quarterly OKR’s and these will be reviewed frequently with your line manager.
As a member of the team, you may be required to mentor junior team members, contribute to technology discussions, support academic and AI community engagements, marketing events, and recruitment activities.
Contact
Find out more about Adarga: https://adarga.ai/careers
Recruitment company statement
We approach everything with transparency and integrity. To avoid wasting anyone’s time, here is our policy on working with recruitment companies: At present, we are not working with any new recruitment agencies, because we only want to work directly with individual applicants who can contact our People Team through careers@adarga.ai
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Science Deep Learning Docker Engineering Helm Kanban Kubernetes Machine Learning Model deployment Model training NLP Pipelines Python RDBMS Research SQL
Perks/benefits: Team events Transparency
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