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ABOUT THE ROLE

We are seeking a highly skilled and innovative Principal Machine Learning Engineer to join our dynamic team. The successful candidate will play a crucial role in developing and
implementing autonomous networking capabilities within our product. This position focuses on integrating Machine Learning (ML) algorithms to create a robust, self-managing,
and intelligent multi-cloud networking solution. The team will investigate a wide range of problems from analysis of customer support calls and logging (LLM and text analysis) to
network traffic optimization (graph ML) and statistical monitoring (anomaly detection).

Responsibilities

• Design, develop, and deploy language models, including LLMs, for autonomous cloud networking.

• Integrate advanced graph ML algorithms to optimize network performance, reliability, and security.

• Develop ML models to forecast and analyze time series data in order to identify anomalies.

• Collaborate with cross-functional teams to understand networking challenges and identify ML-driven solutions.

• Implement scalable and efficient ML pipelines for real-time network monitoring, analysis, and decision-making.

• Conduct research on the latest advancements in ML, AI, and networking to keep our solutions at the forefront of technology.

• Develop and maintain comprehensive documentation for ML models, algorithms, and processes.

• Participate in code reviews, testing, and debugging to ensure high-quality code and system performance.

• Provide mentorship and guidance to associates.

Qualifications

Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field.
8+ years of experience in ML engineering, ideally with a focus on networking or cloud infrastructure.
Strong proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
Experience with LLMs and their integration into larger systems.
Experience with graph ML and time series analysis.
Solid understanding of networking concepts, protocols, and cloud architectures (e.g., AWS, Azure, GCP).
Proven track record of deploying ML models in production environments.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication skills to articulate complex technical concepts to non-technical stakeholders.

Preferred qualifications:

Master's or PhD in Machine Learning, Artificial Intelligence, or a related field.
Experience with autonomous systems or self-managing networks.
Familiarity with reinforcement learning and its application to networking.
Knowledge of network security principles and ML-based security solutions.
Contributions to open-source ML or networking projects.

US Pay Range

The US annual base salary range for this full-time position is $285,000-$300,000 + benefits + 401(k) match + equity. The pay range is determined by the role, work location, job-related skills, level, experience and relevant education. [Certain roles are eligible to earn sales commission, depending on the terms of the applicable plan.] The range displayed is the minimum and maximum target base salary and is applicable only for new hires for the listed position located in the US. Your Talent Advisor can share more details regarding salary ranges, benefits, and equity for your location during the hiring process.

#LI-REMOTE

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BENEFITS

US: We cover 100% of employee premiums and 88% of dependent(s) premiums for medical, dental and vision coverage, 401(k) match, short and long-term disability, life/AD&D insurance, $1,000/year education reimbursement, and a flexible vacation policy.

Outside the US: We offer a comprehensive benefits package which, (subect to regional variations) could include pension, private medical for you and dependents, generous holiday allowance, life assurance, long-term disability, annual wellbeing stipend

Your total compensation package will be based on job-related knowledge, education, certifications and location, per our aligned ranges.

About Aviatrix 
Aviatrix is the cloud networking expert. We’re on a mission to make cloud networking simple so companies stay agile. Trusted by more than 500 of the world’s leading enterprises, our cloud networking platform creates the visibility, security, and control needed to adapt with ease and move ahead at speed. Combined with the Aviatrix Certified Engineer (ACE) Program, the industry's leading multicloud networking and security certification, Aviatrix empowers the cloud networking community to stay at the forefront of digital transformation.

WE WANT TO INCLUDE YOU

We embrace the fact that not everyone’s journey took the same route or started at the same place. If your experience doesn’t quite meet the requirements but the opportunity excites you and you believe you could be great, don’t let that hold you back from applying. Tell us what you CAN bring and what makes you special.

Aviatrix is a community where everyone's career can grow and we want to help you achieve your goals and be “your best YOU,” however that looks. If you're seeking an opportunity where you can be excited to start work every morning with enthusiastic people, make a real difference and be part of something amazing then let’s talk. We want to get to know you and how we could grow together.

Aviatrix, Inc. is an equal opportunity employer and does not make hiring decisions based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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Principal ML Engineer - US Remote

at Aviatrix (View all jobs)

United States

Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or a related field.
8+ years of experience in ML engineering, ideally with a focus on networking or cloud infrastructure.
Strong proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
Experience with LLMs and their integration into larger systems.
Experience with graph ML and time series analysis.
Solid understanding of networking concepts, protocols, and cloud architectures (e.g., AWS, Azure, GCP).
Proven track record of deploying ML models in production environments.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication skills to articulate complex technical concepts to non-technical stakeholders.

Preferred qualifications:

Master's or PhD in Machine Learning, Artificial Intelligence, or a related field.
Experience with autonomous systems or self-managing networks.
Familiarity with reinforcement learning and its application to networking.
Knowledge of network security principles and ML-based security solutions.
Contributions to open-source ML or networking projects.

US Pay Range

#LI-REMOTE

#LI-LD1

BENEFITS

Your total compensation package will be based on job-related knowledge, education, certifications and location, per our aligned ranges.

WE WANT TO INCLUDE YOU

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