Principal Wireless Algorithms Engineer (MAC Layer Scheduling)

Join the Team That's Redefining Wireless Technology

At Tarana, we're more than just a fast-growing tech company—we’re a team of bold innovators on a mission to revolutionize broadband. Our groundbreaking Fixed Wireless Access technology is delivering fiber-class internet speeds worldwide, bridging the digital divide in ways previously thought impossible.

As a Principal Wireless Algorithms Engineer (MAC Layer Scheduling), you will work in a team whose primary responsibility is to bring up and maintain a stable operating platform and build a system for our next-generation Fixed Wireless Access (ngFWA) products.

This role focuses on the MAC scheduler, and you will create algorithms from the ground up to allocate spectrum, time, and data streams across a large-scale deployed network. We are looking for an engineer who can invent and develop algorithms to solve complex, real-world performance challenges. You will dig into field anomalies, customer-reported issues, and large volumes of telemetry data to drive performance improvements, identify potential problems, and design innovative solutions.

The ideal candidate is comfortable working at the edge of what is known, exploring ideas that may not work, learning quickly from failure, and applying strong engineering judgment to know when to pivot. If you enjoy solving difficult problems and providing solutions, this is the role for you. If you want a well-specified backlog and a clear definition of work, this role isn't for you.

What You’ll Do:

• Invent. Solve challenging problems in scheduling, resource allocation, link adaptation, interference management, spectrum coordination, latency, and fairness. Many problems will begin with a hunch or observed performance issue—not a detailed specification.
• Define the problem. Turn ambiguous performance issues into clear, tractable problems, and use sound judgment to determine which ones are worth solving.
• Validate before building. Use simulations, offline analysis, and real field data to evaluate ideas before committing to implementation.
• Design for robustness. Think beyond standard test cases and ensure algorithms behave reliably across a wide range of operating conditions, including difficult-to-reproduce edge cases.
• Ship your work. Write production C++ for the systems you design and stay involved through integration, field validation, and real-world deployment.
• Raise the bar. Review designs and code rigorously, asking hard questions about edge cases, tradeoffs, and failure modes.
• Close the loop. Work closely with systems engineering, DSP, and field teams to understand how algorithms perform in real-world networks at scale.
• Explore new approaches. Evaluate where machine learning can outperform traditional algorithms and understand the practical cost of running models within embedded, real-time constraints.
• Mentor and lead. Help other engineers build strong technical judgment—not just implementation skills.

What You'll Need:

• 12+ years of experience designing algorithms for wireless systems, with significant ownership of scheduler, resource allocation, link adaptation, or related functionality in a production product.
• Master of Science (MS) or doctoral degree (PhD) in Electrical Engineering, Computer Science, or a related field or equivalent work experience.
• Strong foundation in wireless communications, including OFDM, MIMO, beamforming, interference modeling, and an understanding of the practical tradeoffs between theoretical models and deployed hardware.
• Comfort with the mathematics underlying these problems, including optimization, estimation, and probability, along with the judgment to know when a simpler approach is the better engineering solution.
• Strong production-level C++ experience on Linux, with the ability to independently implement complex designs and provide credible, thoughtful code reviews.
• Proficiency with simulation and data analysis tools such as Python, MATLAB, or equivalent.
• A track record of developing and shipping innovative solutions that delivered measurable real-world results.
• Extensive hands-on experience using AI-assisted development tools in real engineering environments.

What Would Make You Stand Out

• Experience with multi-core embedded platforms, real-time constraints, and the tradeoffs of running algorithms inside a frame budget
• Familiarity with machine learning applied to physical-layer or MAC-layer problems, including the practical constraints of on-device inference
• Experience with large-scale field telemetry: designing what to collect, and extracting signal from it
• Background in cellular or Wi-Fi standards work (3GPP, 802.11), particularly scheduling and interference coordination
• Experience building reusable agent workflows, skills, or tooling that raised the productivity of a team rather than just an individual

What we offer:

We don’t just build next-gen wireless technology — we build people.

The salary range for this position is: $185,000 to $240,000
Compensation will be determined based on several factors, including, but not limited to, skill set, years of experience, and the employee’s geographic location.
Tarana provides competitive benefits to employees in this role, including medical, dental, and vision benefits, 401K match, flexible time off, and stock options.

Join Tarana and help shape the future of wireless connectivity.

About Us

Tarana’s mission is to accelerate the deployment of fast, affordable, and reliable internet access around the world. Through a decade of R&D and over $400M of investment, the Tarana team has created and continues to enhance a suite of next-generation fixed wireless access (ngFWA) technologies. Its unique ngFWA platform delivers game-changing advances in broadband economics in mainstream and underserved markets, using both licensed and unlicensed spectrum. Tarana’s ngFWA technology has been embraced by more than 300 service providers in 24 countries. Tarana is headquartered in Milpitas, California, with additional research and development in Pune, India. Learn more at www.taranawireless.com.