This job is closed
We regret to inform you that the job you were interested in has now been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.
About the position
Symend is seeking a highly skilled Senior Machine Learning Engineer to develop and scale machine learning and deep learning projects. The role involves productizing ML models, supporting MLOps, maintaining and enhancing existing models, and collaborating with data scientists and engineers. The ideal candidate should have a strong background in Python development, machine learning, and software engineering, as well as knowledge of deployment practices, version control systems, and CI/CD processes. Additionally, familiarity with ML frameworks, cloud services, and agile/scrum processes is desired. This is an opportunity to work with cutting-edge technology and drive successful ML initiatives.
- Develop ML tools and libraries for training, error analysis, serving, and maintaining ML models
- Write or re-engineer REST APIs in Python for ML models with best coding and engineering practices, unit testing, security, performance, and hardware resource allocation
- Support Machine Learning life cycle management from data preparation to automation of model training, experiment analysis, and model/dataset registry steps
- Assist with development of prompt engineering tasks for large language models (ChatGPT) LLM
- Automate, improve, enhance, and scale MLOps pipelines
- Own, improve, and document CI/CD for deployment of machine learning components and processes
- Research, develop, and scale state-of-the-art technologies in ML and LLMs
- Collaborate with Data Scientists and Data Engineers on building MVPs from POC models and algorithms
- Take initiative in communicating ideas, requirements, and challenges to the team lead and product managers
- BSc in Computer Science, Software Engineering, or a related field.
- Master's degree or certificate in Machine Learning or Data Science would be an asset.
- 3+ years in Python development.
- 3+ years in Machine Learning development.
- 5+ years in Software Engineering development.
- 1+ years in DevOps/MLOps and microservices development.
- Passion for software engineering and machine learning engineering to streamline and automate the end-to-end R&D and production development process.
- Strong software engineering experience in Python, REST API development, and maintenance in a production environment.
- Knowledge of deployment practices such as code profiling, multiprocessing, database, API load/stress testing, unit testing, and API schema validation.
- Knowledge of version control systems and concepts such as Git and GitFlow.
- Knowledge of CI/CD process such as Azure DevOps Pipelines, Github Actions.
- Knowledge of Docker technologies.
- Familiarity with fundamental ML and LLM concepts.
- Familiarity with multiple ML frameworks, such as TensorFlow, Keras, PyTorch, Spacy, and Scikit Learn.
- Familiarity with end-to-end Machine Learning software life cycle.
- Familiarity with cloud services like Azure or AWS.
- Familiarity with Agile and Scrum processes.
- Comfortable with Unix/Linux commands and administration.
- Ability to communicate effectively with technical and non-technical audience.
- Exceptional interpersonal and relationship management skills.
- Eager to learn new concepts and expand their experience in a fast-growing startup.
- Experience with BERT models and Transformers (asset).
- Experience running LLMs (asset).
- Experience with MLOps platforms such as Azure ML, Kubeflow, and MLflow (asset).
- Competitive compensation
- Flexible work environment
- Social Fridays
- Awesome team events
- Being part of a driven and collaborative team
- Trust, accountability, and continuous learning valued
- Opportunity to do work that matters and changes lives
Dev & Engineering
This is some text inside of a div block.