This listing was posted on ApplicantPro.
Machine Learning Engineer - Intelligent Systems
Location:
College Station, TX
Description:
Machine Learning Engineer (On-site) On-site position in College Station, TX. US Persons. Multiple positions. $52k - $85k + Benefits The Intelligent Systems Group at Lynntech is developing new technologies through Research and Development (R&D) to come up with solution to frontier challenges in Artificial Intelligence, Machine Learning (ML), and Data Science. We operate in a collaborative multi-disciplinary environment, where projects lie at the intersection of evolving technical fields, focusing on Intelligence, Surveillance, Reconnaissance (ISR) and Security, Navigation and Tracking, and Healthcare and Life Sciences. Position Summary The Intelligent System Group at Lynntech is a team of about 10 scientists, engineers, and programmers seeking to double its size over the next year. To that end, we are seeking full-time ML engineers to support existing projects while working alongside our scientists and other engineers. ML engineers are responsible for assembling data sets for testing models and methods, finding available models which are appropriate for the data processing needs of a specific project, setting up computational environments, and building and testing models. Due to the exploratory and interdisciplinary nature of our projects, duties associated with ML often overlap and intersect with those from other disciplines, such as data analytics and synthesis, as well as software and algorithm development. Thus, familiarity with disciplines outside of ML are valuable and domain expertise in other fields provides a novel context for application of ML methods. For some of our more nascent projects, pre-existing data sets are not always available, so there is also a strong data acquisition (DAQ) and data synthesis aspect to our work. To that end, some projects involve working with hardware and sensors, most notably cameras. Projects may require operating DAQ systems and going out and collecting field or lab data. Other projects have virtual environments set up in which 3D models and simulations are used for creating training data using rendering engines, physics-based modeling software, and finite element analysis tools. Responsibilities and Opportunities for Experience Machine Learning Train and evaluate neural networks for computer vision tasks, such as object detection. Build a software package that automatically annotates image datasets. Fine-tune pre-trained image classification models to adapt them to project needs. Rapidly prototype and evaluate different models and algorithms. Develop software to automate model hyperparameter tuning and loss function selection. Collect field or lab data using cameras, sensors, and various DAQ systems. Sanitize, organize, and prepare training, validation, and test sets. Evaluate ML training using tools such as precision-recall metrics, ROC curves, and confusion matrices. Troubleshooting and debugging of models and scripts. Software Development Develop demonstration apps to showcase object detection models. Share scripts within a containerized environment with a project collaborator Use version control systems such as Git to track and share software changes. Modify existing Python or C++ code to distribute computations across multiple CPU / GPU cores. Setting up and maintain development environments and coordinating with Lynntech IT to request software and/or installation. Research Given a previously unsolved problem, identify state-of-the-art models, valuable data sources, and apply solutions Explain the results of statistical analysis used to test hypotheses Create synthetic data using parametric or non-parametric methods. Helping in the evaluation of research topics and supporting proposals to topics which require ML Evaluating research topics given group's ML capabilities Eligibility and Qualifications Eligibility: The applicant must be able to provide evidence of being either a U.S. citizen or U.S. permanent resident at the time of application to meet contract requirements. Applicants must have on average 40 hours per week availability. (80 bi-weekly) Job is on-site. After a minimal six-week period, hybrid work may be possible per supervisor discretion. Basic Qualifications: 2+ years relevant ML experience or BS in Computer Science, Statistics, Applied Math, Engineering, or related discipline along with ML project experience Ability to work in teams and juggle multiple, possibly changing, priorities Platform agnostic: should be able to work with Microsoft Windows, Linux, or MacOS. Proficiency with multiple ML techniques including Deep Learning, k-means clustering, SVMs, Tree-based models, Bayesian Classifiers, etc. Proficiency with word processing, spreadsheet, and slide show software (e.g., MS Office) Programming proficiency with languages such as Python, MATLAB, C, and C++ and ability to produce production quality code Experience using Tensorflow and/or PyTorch to implement, train, and tune ML models Mathematics proficiency with algebra, linear algebra and linear systems, graph theory, probability and statistics Proficiency with hyperparameter tuning and/or auto-tuning tools and loss function selection 1-2 years of experience implementing ML tools in academic or professional environments Additional Preferred Qualifications and Valuable Experience: MS, or Ph.D. in Computer Science, Statistics, Applied Math, Engineering, or related discipline Strong technical writing and presentation skills Experience with Deep Learning and Neural Networks such as detectors, classifiers, Generative Adversarial Networks (GANs), Reinforcement Learning, Style Transfer, and related algorithms or architectures. Experience in developing AI solutions for any of the following domains: Computer Vision, Medical Image Processing, Geo-spatial Intelligence, Natural Language Processing (NLP) or Signal Processing. Experience with Android Development Familiarity with Docker or Kubernetes Familiarity with software development, project building, compiling, and library linking, using tools such as CMake and conan Experience with revision control systems such as GIT and SVN Familiarity with GPU parallelization and CUDA Experience with software tools: Image processing tools, such as: Photoshop, Gimp, Paint.net, ImageJ 3D and CAD modeling software, such as: Maya, Blender, Solid Works, Inventor Simulation environments, such as: Unreal Engine, Unity, Ansys, COMSOL Scientific computing software, such as: MATLAB, LabView, Simulink, Octave AI Explainability methods, Adversarial Examples, and evaluation of AI algorithms performance. Experience cleaning up data using statistical tools for outlier removal and bias correction Photography and experience with optics and imaging systems Experience working with hyperspectral image and/or video data Experience with microscopy, satellite and GIS data, astronomical imaging, and medical imaging Game development, Virtual Reality, or Augmented Reality The Team The Intelligent Systems Group at Lynntech is developing new technologies through Research and Development (R&D) to come up with solution to frontier challenges in Artificial Intelligence, Machine Learning (ML), and Data Science. We operate in a collaborative multi-disciplinary environment, where projects often lie at the intersection of different technical fields, broadly falling into one of the three industry domains: Intelligence, Surveillance, Reconnaissance (ISR) and Security Navigation and Tracking Healthcare and Life Sciences Within these domains we work to generate, plan, and execute highly innovative solutions in the fields of AI, state-of-the-art electro-optical/infrared, embedded navigation systems, human-machine interfaces, and other resources to solve real-world problems such as search and rescue, analysis of geospatial data to provide actionable intelligence, terrain monitoring, disaster recovery, computer vision for autonomous vehicles, assistive technologies for disabled users, data analytics, natural language processing, and mobile computing for Internet of Things (IoT) applications. As part of our ongoing research efforts, we continuously evaluate topics from government-released R&D solicitations and write research proposals in response. Upon competitive selection for contract award, such proposals become active research projects. Our team has several such R&D projects running in parallel. Each project is coordinated by one of our Principal Investigators (PI) who are responsible for supervising and delegating workloads between projects and it is common for scientists, engineers, and analysists to be involved in two to three projects simultaneously. Why should you work at Lynntech? Employee Benefits and perks of the position and area: Opportunities to pursue R&D interests through government grants with full support of our Project Management Office (PMO) for assisting with the application process and document submission Benefits: Medical, Dental, Life, Disability, Vision, Retirement and Leave Short commute and low cost of living for the Bryan-College Station area Close proximity to Texas A&M University and frequent opportunities for collaboration with faculty. Opportunity for Career Growth: Your work will have an impact and make a difference in the world: Lynntech employees get to work across various disciplines and are engaged in all aspects of technology development from idea generation to commercialization. Opportunities to own your projects. On-boarding at Lynntech is designed to provide new hires with opportunities to take on more and more responsibilities in our R&D projects, eventually have the chance to lead them. You get the best of both worlds: We offer the infrastructure and stability of an established company as well as the challenge, benefits, and entrepreneurial spirit associated with a small business. Your work will be interesting and varied: You will have the opportunity to be creative and work on a myriad of projects across various industries (defense, energy, aerospace and medical). If you can get buy-in for your idea and procure funding to pursue research, you will get to work on it. You'll be able to contribute to the organization in a variety of ways: You will get to wear a variety of hats in this role. Some examples include core technology strategy development, proposal writing, research and technology development, product development, program management, business development and mentorship of young researchers. A day in the life with the Intelligent Systems Group Our projects lie at the interface between fundamental research and engineering, and we are often adapting ideas from disparate academic fields and finding ways to apply them in various real-world domains. We have several R&D projects running in parallel, and work focus shifts according to different project needs and deadlines. Each project is coordinated by one of our Principal Investigators (PI) who are responsible for supervising and delegating workloads between projects and it is common for scientists, engineers, and analysists to be involved in two to three projects simultaneously. You will start off working on individual tasks and filling in singular needs but over time be given responsibility for developing and maintaining larger pieces of projects and owning your own systems. We encourage our group members' growth and provide opportunities for taking on more responsibility, eventually leading projects and deciding the direction of future research. Our projects leverage the following core disciplines : Computer Vision, Image Processing, and Numerical Methods Machine Learning and Natural Language Processing Simulation, 3D Modeling, and Image Synthesis Remote Sensing and Geospatial Analytics State Estimation, Filtering, and Statistical Analysis Data Acquisition, Synthesis, Wrangling, and Processing Software Development and Sys Admin Research, Proposal Writing, Grantsmanship, and Business Development Even though you will start off focusing on one specific domain, team members are frequently involved on multiple projects with duties that span across these core disciplines. It is perfectly acceptable if find yourself slowly branching out or changing disciplines as your interests change and certain projects gain more traction than others. Branching out takes the form of joining existing projects or working on proposals to start new ones. Each of us is involved to some degree with the evaluation of government-released research solicitations. When batches of solicitations are released by various government entities, like NASA or the Department of Defense, for example, we come together as a team and decide on which ones we should pursue and who will lead efforts on writing proposals to the selected topics. Interview Process After applicants have submitted their application, our interviews follow a four-step process: Pre-screening and request for work sample . If an applicant's resume passes pre-screening, Lynntech will send out a candidate packet which contains information about the company and the team. We will also request a work sample which is demonstrative of the applicant's experience relevant to the job posting. If the work sample demonstrates relevant proficiency in the job domain, Lynntech will continue with scheduling a time for an interview. 1st Interview (Usually Phone/Virtual unless local candidate). [Duration: 1 hr] During this call, both parties will review background information and review eligibility requirements. Company policies, job expectations, work environment, and availability will be discussed. The interview may conclude here if the candidate is no longer interested in pursuing the opportunity or if the candidate does not meet basic eligibility requirements. We will also discuss the different roles in the group and establish the domain specific project needs which we have at that moment and candidate will be asked to rank their experience and comfort level with the various core disciplines . Candidates will be expected to elaborate on their relevant past project experience. Candidate Assessment, Part 1: If both parties choose to continue, candidates will be asked to complete and submit Part 1 of the Assessment which was included in their packets. This assessment covers fundamentals in computer literacy, programming, and mathematics. Lynntech will review the submission and before scheduling a second interview. Part 2 of the assessment is only requested if a second interview is scheduled. 2nd Interview (Usually On-site*) and Part 2 of Assessment. [Duration: 3 to 4 hr] If both parties choose to continue, an in-person interview will be scheduled, and the candidate is responsible for completing Part 2 of the assessment prior to the second interview. The candidate will be notified in advance if an optional domain specific assignment or live coding interview is required. This final step will be comprised of the following: Past Project Presentation/Demo: The candidate will give a 10-15 minute presentation/demonstration of a past personal or professional project which relates to one of our core disciplines . Your presentation should resemble more of a story than an academic talk and it can be an example from your past personal or professional experience. If you have physical or virtual demonstrations at hand, or something interactive, you're encouraged to bring them. It's also beneficial if you have pictures/graphics and videos walking us through your development process and showing the final result. Highlight any problems or challenges you faced along the way and how you overcame them. There will be time at the end for Q&A and open discussion. If you're uncertain about what topic to present on, please reference our technical domains for guidance. Duration: 25 to 45 min Project Domains and Core Disciplines Discussion: We will discuss what the existing project needs are and how the candidate's skill set can best fit the project needs. We will review the various roles, responsibilities, and how the various core disciplines relate to our projects. Duration: 30 to 40 min [Optional] Assessment Review: If reviewers have previously provided a domain specific assignment, candidate answers will be reviewed, and additional questions may be given. Interviewers will assess candidate's ability to reason through challenges and their ability to identify and test their assumptions when approaching problems. Duration: 30 to 60 min [Optional] Live Coding Interview: A live open-book set of coding problems. Candidates will be given programming problems which they must solve. Internet search will be available for looking up information and interviewers will be there to answer questions and help if necessary. This will test not only the candidate's ability to program, but also their ability to search for answers and ask for help and collaborate when appropriate. Duration: 30 to 60 min * For long-distance candidates, this may be a virtual interview. If a job offer is made the candidate will be invited to for an on-site visit before a final response is expected. Interested applicants are encouraged to apply online at www.lynntech.com . Lynntech is an Equal Opportunity Employer M/F/Vet/Disabled. Job Posted by ApplicantPro
Company:
Lynntech
Posted:
December 26 2023 on ApplicantPro
Visit Our Partner Website
This listing was posted on another website. Click here to open: Go to ApplicantPro
Important Safety Tips
- Always meet the employer in person.
- Avoid sharing sensitive personal and financial information.
- Avoid employment offers that require a deposit or investment.
To learn more, visit the Safety Center or click here to report this listing.
More About this Listing: Machine Learning Engineer - Intelligent Systems
Machine Learning Engineer - Intelligent Systems is a Engineering Engineer Job at Lynntech located in College Station TX. Find other listings like Machine Learning Engineer - Intelligent Systems by searching Oodle for Engineering Engineer Jobs.
Machine Learning Engineer - Intelligent Systems is a Engineering Engineer Job at Lynntech located in College Station TX. Find other listings like Machine Learning Engineer - Intelligent Systems by searching Oodle for Engineering Engineer Jobs.