{"id":804056,"url":"https://alion.io/job/zeromark-senior-machine-learning-operations-engineer","title":"Senior Machine Learning Operations Engineer","company":{"id":688608,"name":"ZeroMark","domain":"zeromark.com","url":"https://alion.io/company/zeromark","size_band":"51-200","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Ashby","truth_index":{"grade":"D","score":40,"open_postings":10,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-23T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":154000,"max_usd":280000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":637},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"TensorRT","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-06-11T16:51:16Z","employer_posted_date":"2026-06-11","last_verified_at":"2026-09-23T13:10:34Z","board_verified":true,"closed_at":null,"days_open":104,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":103},"description":"About Us\nZeroMark builds AI-driven counter-drone systems that actually work in combat. No PowerPoints. No hype. Just field-proven technology that saves lives.\nWe've doubled year-over-year for two straight years, winning contracts that prove what we've always known: real innovation happens in the dirt, not in conference rooms. Our systems transform standard weapons into AI-powered platforms that detect, track, and neutralize drone threats-because a $200 drone shouldn't require a million-dollar countermeasure.\nHere's what makes us different: ZeroMark operators don't build from behind screens. You'll validate tech from Blackhawk helicopters, train alongside Tier-1 units (who happen to be our coworkers), and test at legendary ranges from White Sands to the cliffs of Hawaii. When we say field-tested, we mean you'll shoot it, fly with it, and push it to failure. We don't tweet about changing the world-we're too busy actually doing it. Watch us in actionhere. Dark humor required, thick skin recommended.\nIf you want to make an actual impact-and have some unforgettable Tuesday afternoons along the way-let's talk. We're all about delivering practical, field-tested tech, not just theories.\nWhat You'll Do\nDesign, develop, and implement end-to-end machine learning pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.\n\nCollaborate with the general software engineering team to integrate ML models into existing software systems and ensure scalability and maintainability.\n\nWork in conjunction with computer vision specialists to apply and optimize ML techniques for image and video analysis, object detection, tracking, and recognition in defense contexts.\n\nResearch and evaluate new machine learning algorithms, tools, and technologies to enhance our capabilities and solve challenging problems.\n\nPerform rigorous model testing, validation, and performance tuning to ensure robustness and accuracy in real-world scenarios.\n\nContribute to the development of best practices for ML engineering, including MLOps, version control, and reproducible research.\n\nMentor junior engineers and contribute to a culture of continuous learning and knowledge sharing.\n\nCommunicate technical concepts effectively to both technical and non-technical stakeholders.\n\nWhat You'll Need\nEducation: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.\n\nExperience: 5+ years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.\n\nTechnical Skills:\nStrong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).\n\nSolid understanding of core machine learning concepts, including supervised, unsupervised, and reinforcement learning.\n\nExperience with various machine learning model architectures and their application (e.g., CNNs, RNNs, Transformers, decision trees, support vector machines).\n\nFamiliarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).\n\nExperience with MLOps tools and practices.\n\nExperience deploying a variety of edge systems.\n\nExperience with TensorRT and other similar technologies.\n\nDeep knowledge of C++ and Python.\n\nDomain Knowledge:\nExperience or strong interest in defense, aerospace, or related industries is highly desirable.\n\nUnderstanding of the unique challenges and considerations for deploying ML in defense applications (e.g., adversarial robustness, real-time constraints, data security).\n\nCollaboration & Communication:\nExcellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.\n\nAbility to translate complex technical concepts into clear and concise language.\n\nProblem-Solving:\nStrong analytical and problem-solving skills, with a proactive and innovative approach.\n\nAbility to work independently and manage multiple priorities in a fast-paced environment.\n\nBonus Points\nExperience with specific computer vision tasks such as object detection, segmentation, or tracking.\n\nFamiliarity with real-time ML systems and embedded systems.\n\nContributions to open-source projects or publications in relevant fields.\n\nWhat We Offer\nCompetitive salary, equity, and benefits package.\n\nOpportunity to work on cutting-edge technology with a significant impact on national security.\n\nA collaborative work environment that values innovation.\n\nProfessional development opportunities and career growth.","description_format":"text","description_chars":4548,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity","Professional development"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Design & Creative","Robotics"],"lifecycle":[{"event":"open","at":"2026-09-12T09:11:36Z"}],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.26,"p_room":0.28,"age_days":103,"expected_fill_days":43,"reasons":["conf:0","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-09-23T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/zeromark-senior-machine-learning-operations-engineer","json_url":"https://alion.io/job/zeromark-senior-machine-learning-operations-engineer.json","meta":{"generated_at":"2026-09-23T18:29:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}