Requirements
- Interview with Hiring Manager (45min)
- Take-home assessment (3 hours) + Technical Interview to discuss results (1 hour)
- On-site interview to meet the team (full-day)
Pay Range/Benefits:
- $300k - $350k (all in)
- Relocation package available (within the US)
- Full health, dental, and vision insurance
- Unlimited PTO
- Paid relocation
- Company gym membership
- Free lunch every day
IMPORTANT: This role requires US citizenship due to federal contracting guidelines.
What you’ll be working on
Qualifications
- MS or equivalent experience in Computer Science, Data Science, Mathematics, Statistics, Physics, or related field. PhD or equivalent experience preferred. Candidates still in their graduate program will be considered.
- Strong proficiency in at least one popular ML framework, e.g. Tensorflow or Pytorch. The ideal candidate will have hand-rolled their own ML training environment, even if in a very limited capacity.
- Strong proficiency in coding and data science.
- End-to-end proficiency at the model engineering process -- from data acquisition, storage, processing, and interface design, to model architecting and training, to local or cloud model deployment.
- Proficiency in Probability Theory and other mathematical areas relevant to ML.
- A demonstrable track record of high-quality work in architecting and training neural networks. The ideal candidate will have a publication record demonstrating the ability to make novel contributions.
- Significant experience with computer vision models, natural language models, multimodal data and/or sensor fusion.
- Excellent communication skills, and the ability to work effectively in a team.
👉Matcher tips:
- Ensure your resume clearly showcases the skills and qualifications needed for this role.
- Highlight any relevant experience you have gained working in MAANG companies, early-stage startup or similar environments. These experiences can be particularly valuable.
- Carefully read the job description, paying special attention to the requirement for a generalist skillset. Tailor your application to demonstrate your generalist experience.
- When answering screening questions, highlight your qualifications listed under the "preferred" section of the job description. Show how you meet these preferences.
- To set yourself apart from other candidates, refrain from using AI-generated responses. Showcase your unique qualities and experiences instead.
- This is a hybrid role, and be prepared to discuss how your skills and background align with the diverse aspects of the job.
- Note that this role offers a relocation package to candidates who match the qualifications of the position. Be prepared to discuss your willingness and readiness to relocate if applicable.
- IMPORTANT: This role requires US citizenship due to federal contracting guidelines.