Senior Software Engineer, Research
Wispr.ai
Software Engineering
San Francisco, CA, USA
Posted on Tuesday, November 16, 2021
Wispr is building a more natural way to interact with technology with neural interfaces. We're building a team of world-class scientists, engineers, and product designers to make that a reality.
So far, we've raised 14.6M from top-tier VCs like NEA and 8VC. Our angels and advisors include Chester Chipperfield (product lead for the first Apple Watch), Ben Jones (COO, CTRL-Labs), Dave Gilboa (CEO, Warby Parker), and Jose Carmena (Berkeley professor; co-CEO iota). Our founders are Stanford alums and have previously sold a company and run a team at a deep tech startup with over 100M in funding.
We're hiring in SF Bay Area / Remote.
As a software engineer on the research team at Wispr, your primary responsibilities will be to work closely with machine learning scientists and neuroscientists to craft algorithms to decode surface electromyography (EMG) and other neural signals. You will own data collection software for R&D, the data pipelines for rapidly iterating on the R&D side, and increasing the performance and throughput of machine learning model training.
Come join us and make magic happen.
Core Job Responsibilities
- Write clean and performant code to train ML models, focusing on throughput, stability, and ML metrics
- Implement data collection frameworks, curate datasets, perform pre-processing/feature extraction, and build machine learning models for EMG decoding
- Architect and deploy an infrastructure for researchers to iterate with the required data models and APIs, including building data pipelines
- Setup testing, best engineering practices for the research engineering team
- Rapidly iterate and extend (novel) processing and analysis algorithms
- Collaborate with neuroscientists, machine learning experts and user researchers to unlock and perfect new capabilities to build interactions upon
Required Knowledge/Skills, Education, And Experience
- MS or BS in computer science, machine learning or related engineering field
- 3+ years hands-on relevant engineering experience in machine learning, signal processing
- Experience working in research oriented environments, reading papers, and contributing to novel research
- Experience setting up data processing / ML pipelines and infrastructure, ideally for a research-based environment.
- Proficient in Python and machine learning libraries (SciKit-learn, SciPy, NumPy)
- Experience with deep learning frameworks (PyTorch, Tensorflow)
- Experience with cloud computing (AWS, Google Cloud)
- Organized, self-directed, efficient and able to manage priorities and expectations
- Experience working collaboratively with teams: we believe in working collectively towards a common goal
Nice to have Knowledge/Skills, Education, And Experience
- PhD in computer science, machine learning or related engineering field
- Published papers in machine learning
- Experience working with bio-signals (EMG, EEG, EKG, etc), medical devices, or real world noisy data
- Experience optimizing GPU performance for ML model training
- Experience working with speech recognition, audio data, generative models, or NLP
Why Wispr?
• Design the next generation of personal computing in a creative and innovative environment.
• Headquarters in an open, green, and bright office in South San Francisco with water views
• Work closely with a world-class team.
• Flexible work arrangements to support you in working in the way that you work best.
For full-time employees:
• Generous health, dental, and vision coverage
• Generous parental leave, unlimited PTO (we encourage taking days off!)
• 401k match
• Commuter benefits
• Relocation assistance
• Total compensation for this position may also include stock options and other potential future incentives
At Wispr, diversity is important to us.
At Wispr, we believe that true innovation starts from people from diverse backgrounds coming together, bridging ideas, and collaborating. Wispr is proud to be an Equal Employment Opportunity employer and is committed to providing an environment of mutual respect where employment opportunities are available to all applicants and teammates without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law.
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