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R&D Software Lead
1 month ago
About Wispr: We've raised $26.5M 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.
As the technical lead of the research software 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. If you enjoy building user centric software to accelerate R&D, you're a great fit for this role
Come join us and make magic happen. Core Job Responsibilities
- Architect the R&D codebase and lead the technical design of the R&D software
- Build scalable abstractions for accelerating data science and ML
- 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 processing time series and natural language data.
- Architect and deploy the infrastructure & data pipelines for researchers to iterate with the required data models and APIs
- Setup testing, best engineering practices for the research engineering team
- Rapidly iterate and extend (novel) processing and analysis algorithms
- Collaborate with neuroscientists, ML engineers, and interaction designers to unlock new capabilities to design the most natural and seamless human-computer interactions
- MS or BS in computer science, machine learning, or related engineering field
- 3+ years of 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 (e.g., Airflow, Mage, Dask, etc.).
- Proficiency in Python, ML libraries, and deep learning frameworks (SciKit-learn, SciPy, NumPy, 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
- Ph.D. 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 noisy real-world data
- Experience optimizing GPU performance for ML model training
- Experience working with speech recognition, audio data, generative models, or NLP
Why Wispr? • Build magic and see the excitement spark in every users' eyes • Design the next generation of personal computing in a creative, innovative, and collaborative environment • Do the best work of your life 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 with 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.
