Location: Seattle, WA (onsite)
Salary: $150-250k+ & Equity
Alldus are currently working with an exciting software start-up to help hire for a Computer Vision Engineer. This is a great opportunity to work for a growing start-up to have a real impact on their internal team. The role will be located in Seattle, WA and will have you working with an ambitious team who have achieved a lot in a short period of time.
- Working as part of the engineering team to research, develop and integrate computer vision methods
- Work on tracking, identifying and traceability products to be deployed on a large scale
-Improve the digital fingerprint for multiple fortune 500 companies
- Collaborate with team and wider organization to execute business goals and complete projects with specific timeframes
- Must be willing to work on site in Seattle 5 days a week
- 10+ years of experience working in Computer Vision
- Masters or Ph.D. in ML or a similar field is highly desirable
- Experience working with start ups / working with small/medium sized engineering teams is highly desirable
The successful applicant will be responsible for developing and deploying models that will enable the processing of large amounts of data from various sources to uncover insights that will help to discover new drugs. You will work closely with a team of data scientists and engineers to ensure that the models are optimized for accuracy and performance.
- A degree in computer science, engineering, or a related field
- At least 3 years of experience developing computer vision algorithms
- Expertise in deep learning and machine learning
- Knowledge of computer vision frameworks such as OpenCV, TensorFlow, and PyTorch
- Experience with supervised and unsupervised learning algorithms
- Excellent problem-solving and communication skills
If you are looking for a challenging and rewarding opportunity to join a forward-thinking company, please submit your résumé today. We look forward to hearing from you.
This successful applicant will be responsible for the design and implementation of cutting edge computer vision algorithms to improve medical imaging applications. The successful candidate will have a passion for research, development and implementation of medical imaging technologies and have the ability to work collaboratively with a variety of stakeholders.
- Bachelor's degree in Computer Science, Computer Vision or related field
- 5+ years' experience in computer vision, image processing and machine learning
- Extensive knowledge of computer vision libraries and frameworks such as OpenCV and TensorFlow
- Experience in medical imaging and/or medical device development
- Ability to design, develop and implement computer vision algorithms
- Strong communication, problem solving, and organizational skills
- Self-motivated and able to work independently
Salary is competitive and negotiable depending on experience.
If you are a talented Computer Vision Engineer, please apply today for consideration. We look forward to hearing from you.
- Financial organization
- Large corporation
- Many growth opportunities
- Corporate Analytics group
- Offer innovative data-driven solutions
- Delivering new predictive analytics and AI solutions
- Work with many different forms of data such as social media, medical information, credit history, demographics & more
- Methodology review
- Leadership responsibilities
- Review model designs, methodology and features
- Model validation
- Review model performance
- Build challenger models as needed to compare with models being validated
- Writes model validation reports
- Summarize findings from validations
- Maintain inventory of all statistical models
- Education: Master's or PhD in statistics, computer science, mathematics, economics, engineering, or other similar technical fields
- 3+ years industry work experience
- Statistical model risk management
- Experience in statistical modeling techniques
- Strong programming background using Python, R, and SQL
Our client has created a platform that leverages Artificial Intelligence to assist workers in reducing risk and planning, bidding, and building more efficiently. This is an exciting opportunity to work on a greenfield project building a truly innovative and category-defining artificial intelligence product in one of the world’s largest and most important industries.
Location: Flexible - Prague, San Francisco, Remote
- This high-profile role will work closely with key stakeholders and c-suite to have an outsized impact on our product. Some of the work you’ll be doing includes:
- Working with our current Constraint Propagation Problem solver: 1) Optimizing and extending existing constraint implementations; and 2) Designing and introducing new constraints
- Research and prototyping of our next generation of CSP solver
- Designing, prototyping, and testing of the combinatorial optimization algorithms and participating in turning them into production software in cooperation with the rest of the Engineering team
- Leading a team of engineers
- MS+ degree in Computer Science or equivalent
- Deep knowledge of combinatorial optimization algorithms
- Practical experience with constraint programming/constraint planning
- Proficiency in at least one of the following: Python, C/C++, Java/Scala/Kotlin
- Experience working with IBM ILOG CPLEX or Google OR-Tools
- Practical knowledge of software industry standards (version control, TDD, SQL/NoSQL databases)
Join a team of data scientists building a robust computational platform for advancing the R&D of new medicines. This is an exciting opportunity to work across traditional industry boundaries in a fast-paced startup environment, with a diverse array of data spanning biology, computational chemistry, imaging, electronic medical records, text notes, clinical trials and data from their labs.
About The Role
Our client are looking for an experienced Senior/Staff Machine Learning Engineer to design and implement solutions to real-world small-molecule modeling problems to advance computationally accelerated drug development programs. You will apply and enhance the capabilities of their AI-based platform to advance real-world, active drug development programs. Successful candidates must be committed to working with a diverse set of scientists, entrepreneurs, and domain experts in ways that cut across traditional industry boundaries in a fast-paced startup environment.
Day to Day
- Work with data scientists, researchers, product teams, and other domain experts to build solutions to complex data-oriented problems;
- Design, develop, and scale data curation and modeling pipelines for our large-scale, high-throughput applications.
- Train, assess, deploy, and interpret statistical machine learning models that inform and advance our programs.
- A PhD (or Master’s with experience) in Computer Science, Data Science, Bioinformatics or related technical / computational/ quantitative field;
- Experience applying standard statistical analysis and machine learning techniques, such as generalized linear models, kernel methods, ensemble methods, neural networks, and demonstrated impact solving real problems with clear business significance.
- Strong familiarity with the various tools and environments, such as shell, Python/R, and other scripting languages, you have experience using HPC/grid/cloud computing environments, programming against API services, accessing data from a heterogeneous mixture of flatfiles, SQL relational databases, noSQL/JSON object storage, and/or RDF/OWL triple-stores - beyond a fundamental comfort zone
- Software engineering experience across multiple languages such as Python, Java, R
- Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results; and the ability to also condense, summarize, and synthesize those results into informative and actionable presentations to less technical audiences.
- Strong personal project management skills with significant practical experience managing your time split between multiple, parallel projects; experience with Agile processes and frameworks for team collaboration (e.g. Kanban, Atlassian tools)