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Machine Learning Engineer Momentum IO. . We are witnessing first-hand how Machine Learning is transforming entire industries, . automotive. , . healthcare. , . medical device industries. , and . media and entertainment. being just a few. At HTEC, we have a number of amazing experts in this domain, and now we are looking to make our ML team even stronger. If you want to be a part of the ongoing ML revolution and grow together with our experts, read the description below and do not hesitate to apply.. This is a remote position. However, you must be available during working hours EST or PST, aligned with our New York or Silicon Valley offices. Working out of one of our offices is also a possibility. We are looking for FTE. Travel to customer or other work-related locations is expected and is expected to be <20%.. Requirements. Key responsibilities:. . Designing and building machine learning solutions for a given problem, then evaluating and presenting the results. . Data acquisition, exploration, cleaning, augmentation, and visualization. . Designing, conducting, and tracking experiments in different domains. . Designing, training, fine-tuning and deploying custom and existing machine learning models. . Analysing and addressing the errors of applied machine learning models and algorithms. . Working on solution productization, high-level design, and low-level implementation . . Driving the technical quality of a solution and managing technical debt. . Ensuring that the solution is well-documented and presentable to stakeholders. . Participating in the technical investigation (Spike) and prototyping (PoC). . Communicating and collaborating with engineering teams, product teams, and stakeholders in all project phases. . Required qualifications:. . Demonstrated proficiency in designing and delivering robust and scalable distributed systems in production. . Proficient in Python and experienced with object-oriented programming, clean coding, and version control. . Proficient in:. . supervised and unsupervised machine learning. . (hyper)parameter optimization techniques. . . . Experienced in:. . utilization of deep learning models for given task. . transfer learning and/or fine tunning. . model compression techniques. . model explainability techniques. . feature engineering. . . . Proficient in at least one of the commonly used frameworks – TensorFlow, PyTorch, Keras, scikit-learn, etc.. . Experienced in model versioning and experiment tracking/reproducibility tools.. . Experienced in working with structured and unstructured data, as well as relational and non-relational databases. . Experienced in cloud platforms/on-premise and containerization. . Experienced in algorithmic complexity, GPU/CPU utilization, and I/O bandwidth. . Creating pragmatic technical documentation with well-understood diagrams. . Ability to explain technical points using business language and presentations. . Nice to have:. . Striving for constant improvements in solution design. . Keeping up with the new trends in the field. . Experience in working with some of the following domains: Computer Vision, NLP, or signal processing. . Benefits. You get to shape the products of the future, your actionable insights drive key business decisions, and better product experiences globally for the millions, if not billions, that our work touches. Start-ups, scale-ups, unicorns, and $b companies all need your insights. No year is the same.. The Perks. . Core Contribution—Small team means big impact. Every team member’s contribution has a tremendous impact on the project and our clients. . Autonomy—Our staff own their work, and you will have autonomy over how to get it done. . Project Diversity—In a months span, you may work on the next mobile social network, internet of things product, ad platform, or financial services product. . Occasional travel to clients from around the world, we often conduct our project kick-offs on-site.. . Competitive salary & benefits!. . .