Senior Machine Learning Engineer

At Novus, we're not just adapting to the AI revolution, we're leading it. We are an innovative startup based in Istanbul and Boston, specializes in hybrid and on-prem Large Language Model (LLM) services tailored for businesses grappling with data privacy and regulatory challenges. Our AI solutions are designed to seamlessly integrate into existing operations, providing enhanced productivity and sector-specific insights while ensuring full GDPR compliance.

Our offerings include a suite of AI agents that function like team members, capable of collaborating and fine-tuning themselves autonomously to optimize performance across various domains such as sales, finance, and content generation. With a focus on industries handling sensitive data, Novus enables businesses to leverage powerful AI tools without the need for extensive coding or AI expertise.

This position is a hybrid one with the schedule of three days onsite in our Istanbul office and remote the rest of the days.

*How You’ll Make An Impact*

(Note: this is a Machine Learning Engineer position, focused on developing our product's ML-based features and capabilities. We have separate positions for Data Scientist and Software Engineer)

We are seeking a skilled Machine Learning Engineer with a strong background in research and practical lab experience to join our dynamic team. As a pivotal member, you will contribute to the development and implementation of advanced machine learning models, particularly in the domain of natural language processing. The ideal candidate should have hands-on experience with PyTorch, spaCy, and the Hugging Face Transformers library, along with a proven track record of research within a lab environment.

*Responsibilities*

1. Lab-Based Research: Utilize your research experience gained in a lab setting to contribute valuable insights and methodologies to enhance our machine learning projects.

2. Model Development: Design and implement innovative machine learning models, focusing on natural language processing, and address practical challenges with real-world applications.

3. Algorithmic Exploration: Innovate and experiment with machine learning algorithms, exploring new approaches to improve model performance and capabilities.

4. PyTorch Proficiency: Demonstrate strong proficiency in utilizing PyTorch for both research and practical model development, ensuring a robust understanding of underlying principles.

5. NLP with spaCy: Apply advanced natural language processing techniques using spaCy for tasks such as tokenization, entity recognition, and part-of-speech tagging.

6. Hugging Face Transformers Library: Leverage the Hugging Face Transformers library for model development, fine-tuning, and integration into applied projects.

7. Data Experimentation: Work with diverse datasets, employing advanced data processing techniques to extract meaningful insights and patterns.

8. Collaborative Contribution: Collaborate with interdisciplinary teams, actively contributing research-driven insights to cross-functional projects alongside data scientists, software engineers, and domain experts.

*Qualifications*

1. Education: Bachelor's degree in Computer Science, Machine Learning, or a related field with a strong emphasis on practical research experience in a lab setting.

2. Experience: Proven hands-on experience with machine learning research, with a focus on natural language processing, gained through lab work or relevant projects.

3. Technical Skills:

- Proficiency in PyTorch for research and model development.

- Practical knowledge of natural language processing using spaCy.

- Hands-on experience with the Hugging Face Transformers library.

- Hands-on experience with Langchain, Langsmit, Llama Index

- Hands-on experience with optimization engines such as vLLM, ctransformers, and TGI.

- Solid understanding of machine learning theory and principles.

4. Programming Languages: Proficiency in Python and familiarity with relevant libraries and frameworks.

5. Communication Skills: Strong communication skills to effectively convey research findings, insights, and technical concepts within a collaborative team environment.

6. Problem Solving: Strong problem-solving skills with the ability to approach challenges creatively and contribute to the development of practical solutions.

If you are a results-oriented Machine Learning Engineer with hands-on research experience, we encourage you to apply and be a valuable part of our innovative and collaborative team.

*What does the hiring process look like?*

* Initial call with HR

* Call with CTO

* Call with Chief R&D Officer

* Technical Assessment to show your skills (Home Test or Live Coding)

* Debrief of your Tech Assessment with Chief R&D Officer

* A potential final Interview with CTO and HR

*What are you waiting for!*

At Novus, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation and collaboration, we can't wait to welcome you to Novus! And if you’d like to learn even more about working here, you can visit our Novus LinkedIn page.