Machine Learning Engineer

Interviews can be hard, especially at top tech companies like Google, Facebook, and Netflix. Many candidates fall short simply because they aren't adequately prepared. That's where we come in. Our acclaimed courses specialize in interview preparation and transitioning into high-demand tech fields such as AI, ML, and Data Science. At Interview Kickstart, current and former hiring managers have guided over 17,000 tech professionals through transformative career journeys, ensuring their success in landing coveted positions. Think of us as "the everything store" for career transitions and interview skill development.

We have a structured approach to interview success, which includes:

• Career Accelerator Course
• Comprehensive end-to-end courses and platform
• A roster of over 600+ instructors from leading Silicon Valley companies like Google, Facebook, Amazon, and Netflix
• A holistic approach that includes live classes, mock interviews, personalized coaching, resume refinement, career strategies, and invaluable referrals

What's more exciting is that we are completely remote and hiring the best people we can find regardless of geography.

As a Machine Learning Engineer at Interview Kickstart, you will play a crucial role in developing and deploying cutting-edge AI/ML solutions that enhance our platform and improve the learning experience for our students. You will work closely with data scientists, engineers, and product managers to build and scale robust and impactful machine learning models.

What will excite us:

• 3.5+ years of full-time experience as an ML engineer at tier-1 product-based companies.
• Hands-on experience fine-tuning open-source large language models (LLMs) and successfully deploying and maintaining them in scalable production environments on cloud platforms (e.g., AWS, Azure, GCP).
• Hands-on experience building statistical and machine learning models.
• Proven expertise in traditional machine learning methods (e.g., regression, classification, clustering, tree-based models) and deep learning techniques (e.g., neural networks, CNNs, RNNs).
• Proficiency in Python.

Good to have :

• Excellent communication skills, with the ability to present insights clearly to both technical and non-technical audiences.
• A deep understanding of core concepts in statistics, probability, linear algebra, and calculus.
• Strong quantitative abilities, typically supported by an advanced degree (masters or PhD) in fields like Machine Learning, Statistics, or Mathematics.
• Contributions to open-source ML projects.

What will you be doing? :

• Collaborate closely with stakeholders to understand business challenges deeply and translate these challenges into well-defined machine learning problems and actionable project requirements to drive business growth and enhance learner experiences.
• Leverage your expertise in statistical modeling, machine learning, and generative AI/LLMs to research and design optimal solutions for the identified machine learning problems.
• Work closely with fellow developers to build and iterate optimal solutions for the identified machine learning problems.
• Take ownership of deploying the developed machine learning solutions, including fine-tuned LLMs, into scalable production environments (on cloud platforms like AWS, Azure, GCP) and ensure these deployed solutions are effective.
• Staying informed about recent developments in AI/ML, including key publications, best practices, evaluation methodologies, technology stacks, and relevant tools.

What would excite you?

• Complete ownership
• Experiment, fail and learn.
• High pedigree, high calibre team.
• Contribute to every area of our business. Have a real impact on your work
• Top-of-the-line compensation.