DescriptionTyto Athene is seeking a driven and adaptable
Machine Learning Engineer to help shape the future of cybersecurity through automation and machine learning. This role is an opportunity to work across diverse environments-supporting internal product teams, commercial security clients, and U.S. federal customers-while solving meaningful problems with cutting-edge tools and research. At Tyto Athene, innovation meets mission-critical impact. Join a team where your ideas lead to real-world solutions for government and commercial partners. Work remotely with talented engineers, grow your skills, and help us redefine what's possible with automation.
Responsibilities:- Serve as a subject matter expert in Machine Learning and its applications in Cyber Defense, researching and implementing differentiating and novel ML-based solutions to problems SOCs face.
- Developing agentic solutions for Cyber Incident Response.
- Solve complex security and architecture challenges with creativity and precision, with a focus on real-time performance and scalability.
- Identify and recommend improvements to architectures, especially in secure environments.
QualificationsRequired:- U.S. Citizenship (required for federal projects)
- 3+ years of experience with ML
- 3+ years of experience with Cybersecurity, (purple preferred)
- Strong MLOps skills and understanding of the severity of risks such as semantic drift in a security-oriented system.
- Experience developing pipelines that feed to an SOC, ideally an active system such as anomaly detection or IDS rather than just a static or periodically updated dashboard.
- Proficiency with major cloud platforms, such as AWS, Azure and GCP
- Excellent problem-solving, communication, and collaboration skills
- Ability to work independently with distributed teams in a fast-paced, agile environment
- Eagerness to learn new technologies and drive innovation
Desired:- Passionate about cybersecurity and the impact AI will have on the speed and scale of the industry.
- Understands ML theory outside of the current trends, e.g. knows pre-LLM NLP theory and how approaches such as genetic algorithms and energy-based models work.
- Exposure to DoD NetSecOps, even if only as a compliant, s.t. the applicant has an understanding of where the focuses are in DoD network security and what could help them.
- Understands DoD and federal compliance and expectations with regards to security.
- Understands more sophisticated and still-experimental ML approaches such as world models, neuro-symbolic learning, spiking neural networks, experimental RL objectives such as curiosity or information density, etc.
Compensation:- Compensation is unique to each candidate and relative to the skills and experience they bring to the position. This does not guarantee a specific salary as compensation is based upon multiple factors such as education, experience, certifications, and other requirements, and may fall outside of the above-stated range.
Benefits:- Highlights of our benefits include Health/Dental/Vision, 401(k) match, Paid Time Off, STD/LTD/Life Insurance, Referral Bonuses, professional development reimbursement, and parental leave.
