Machine Learning Engineer
Actively Hiring
Full-time Posted 2 months ago
Responsibilities
- check_circle Candidates are expected to be familiar with the motions of a classical Machine Learning workflow, and support the team with some of the following tasks: Dataset Creation. Data Exploration/Visualization. Literature Review. Data Wrangling. Implementation and Training of Appropriate Models from Literature. Characterization of Error in Models. Iterative Optimization of Models.
- check_circle Dataset Creation.
- check_circle Data Exploration/Visualization.
- check_circle Literature Review.
- check_circle Data Wrangling.
- check_circle Implementation and Training of Appropriate Models from Literature.
- check_circle Characterization of Error in Models.
- check_circle Iterative Optimization of Models.
- check_circle On the engineering side of development, the Machine Learning Engineer will have the ability to be hands-on by: Creating training and preprocessing pipelines for faster experimentation. Creating algorithmic modules to interface your Models output with business requirements. Integrating their code to a larger codebase. Putting your model into production using AWS or GCP.
- check_circle Creating training and preprocessing pipelines for faster experimentation.
- check_circle Creating algorithmic modules to interface your Models output with business requirements.
- check_circle Integrating their code to a larger codebase.
- check_circle Putting your model into production using AWS or GCP.
Basic qualifications
- BS. in Computer Science, or related field.
- 3+ years of professional Software Development experience in Python.
- Mastery of Deep Learning fundamentals and statistics underlying Machine Learning.
- History of software projects putting Machine Learning systems into production in any capacity.
- History of software projects in general.
- Deep personal interest with the complete state of the art in a subfield of Machine Learning Research.
- Ability to work independently, and within a team.
- Ability to communicate effectively with non-technical stakeholders and supervisors.
- Prior project experience combining two or more of the following in a production setting: Unsupervised or Semi-supervised Learning. Convolutional Architectures. Autoencoders. Recurrent Architectures for Time-Series Applications. Transformer Architectures for Natural Language Processing. Generative Adversarial Architectures.
- Unsupervised or Semi-supervised Learning.
- Convolutional Architectures.
- Autoencoders.
- Recurrent Architectures for Time-Series Applications.
- Transformer Architectures for Natural Language Processing.
- Generative Adversarial Architectures.
Preferred qualifications
- MS. or PhD in Machine Learning, or related field
- Extensive AWS or GCP experience putting scalable Machine Learning systems into production.
- Experience working with extremely high volume / high throughput data in a data lake / data warehousing / training / production environment.
- Has implemented cutting edge methods (e.g. a custom layer) from recent Machine Learning publications / conference proceedings and has done so in PyTorch or Tensorflow.
- Publications in AI/ML journals or conferences.
Tags & Focus Areas
Fulltime Machine Learning Deep Learning Ai
About Eccalon
We are seeking a skilled Python Developer to join our team, working with machine learning to build innovative solutions. This role is ideal for someone with a passion for developing advanced systems and applying machine learning techniques to complex, data-driven challenges. As part of our team, you will work on cutting-edge projects that require the application of the latest research in machine learning and deep learning.