Android AI ML Engineer - Infrastructure

TITLE: Android AI ML Engineer - Infrastructure

POSITION TYPE: Full Time (W2)

LOCATION: Mountain View, CA

ABOUT
WorldLink:

WorldLink
is a rapidly growing information technology company at
the forefront of the tech transformation. From custom
software development to cloud hosting, from big data
to cognitive computing, we help companies harness
and leverage today’s most cutting-edge digital
technologies to create value and grow.

Collaborative. Respectful. Work hard Play hard. A place to
dream and do. These are just a few words that describe
what life is like at WorldLink. We embrace a culture of
experimentation and constantly strive for improvement and
learning.

We take
pride in our employees and their future with continued
growth and career advancement. We put TEAM first. We are a
competitive group that like to win. We're grounded by
humility and driven by ambition. We're passionate, and
we love tough problems and new challenges. You don't
hear a lot of "I don't know how" or "I
can't" at WorldLink. If you are passionate about
what you do and having fun while doing it; tired of rigid
and strict work environments and would like to work in a
non-bureaucratic startup cultural environment, WorldLink may
be the place for you.

For more
information about our craft, visit .

WHO
we’re looking for:

We are
looking for an Android AI ML Engineer - Infrastructure who will be responsible for developing advanced on-device machine learning systems that enable secure, adaptive, and scalable intelligence across mobile devices. The role emphasizes building intelligent, adaptive, and privacy-preserving ML systems that operate efficiently within the constraints of mobile environments. The ideal candidate will have strong experience in designing real-time, context-aware inference systems that can respond dynamically to local data patterns and behaviors.

Role
and Responsibilities:

• Design, develop, and deploy on-device machine learning models optimized for Android, ensuring low latency and minimal resource consumption.
• Build robust and scalable ML pipelines using Android-native frameworks such as:

• TensorFlow Lite
• ML Kit (including GenAI APIs)
• MediaPipe
• PyTorch Mobile

• Implement local signal aggregation and real-time pattern recognition logic to enable responsive in-app actions driven by on-device inference.
• Architect systems that support telemetry, secure logging, and privacy-first feedback collection for monitoring and evaluation.
• Apply model compression and optimization techniques (e.g., quantization, pruning, distillation) to meet mobile performance constraints.
• Develop secure, privacy-first solutions where all data processing and ML inference occur strictly on-device, with no external data exposure.
• Enable mechanisms for continuous local learning and model updates using device-resident data and signals, without compromising privacy.
• Ensure integration with Android’s security model and collaborate with platform and product teams to deploy AI features safely at scale.

Required Experience and Education:

• 5-7 years of experience with a Masters degree, 3+ years of experience with a PhD.
• Proven experience in Android development (Kotlin/Java) is a plus, with strong understanding of system architecture, resource management, and performance tuning.
• Hands-on expertise with on-device ML frameworks including TensorFlow Lite, ML Kit, MediaPipe, and PyTorch Mobile.
• Solid foundation in machine learning and signal processing techniques, such as time-series modeling, clustering, classification, and real-time event detection.
• Strong knowledge of mobile data handling and Android security practices, including permissions, sandboxing, and secure data storage.
• Understanding of privacy-preserving learning techniques and data governance in mobile environments.
• Familiarity with secure data handling on Android, including encrypted storage, permissions, sandboxing, and secure compute enclaves.
• Experience with telemetry systems and evaluation pipelines for monitoring model performance on-device at scale.

Necessary Skills and Attributes:

• Self-motivated
  individual with the ability to thrive in a team-based or
  independent environment.
• Detail-oriented with strong
  organization skills.
• Ability to work in a
  fast-paced environment.
• Limited supervision
  and the exercise of discretion.

Preferred Qualifications:

• Experience building ML-driven mobile applications in domains requiring user personalization, privacy, or security.
• Understanding of real-time data processing and behavioral modeling on resource-constrained edge devices.
• Knowledge of on-device learning techniques, federated learning, or personalization methods.
• Prior contributions to systems using federated learning, differential privacy, or local fine-tuning of models is a plus.
• Experience with backend infrastructure for model management (e.g., model registries, update orchestration, logging frameworks) is a plus.
• Prior work with anomaly detection or behavioral modeling in resource-constrained environments is a plus.
• Experience developing responsive systems capable of monitoring local context and dynamically triggering actions based on model outputs is a plus.
• Experience optimizing models for ARM architectures is a plus.

Physical Demands:

The
physical demands described here are representative of
those that must be met by contract employee to
successfully perform the essential functions of this
job. Reasonable accommodations may be made to enable
individuals with disabilities to perform the essential
functions.

While
performing the duties of this job, the contract employee is
occasionally required to stand, clean, crawl, kneel, sit,
sort, hold, squat, stoop, stand, twist the body, walk, use
hands to finger, handle, or feel objects, tools or
controls, reach with hands and arms, climb stairs or ladders
and scaffolding, talk or hear, and lift up to 20 pounds.
Specific vision abilities required by the job include
ability to distinguish the nature of objects by using the
eye. Operate a computer keyboard and view a video display
terminal between 50% - 95% of work time, including prolonged
periods of time. Requires considerable (90%+) work utilizing
high visual acuity/detail, numeric/character distinction, and
moderate hand/finger dexterity.

Performs
work under time schedules and stress which are normally
periodic or cyclical, including time sensitive deadlines,
intellectual challenge, some language barriers, and project
management deadlines. May require working additional time
beyond normal schedule and periodic travel.

WHAT
we’ll bring:

During
your interview process, our team can fill you in on all the
details of our industry-competitive benefits and career
development opportunities. A few highlights
include:

• Medical
  Plans
• Dental
  Plans
• Vision Plan
• Life &
  Accidental Death & Dismemberment
• Short-Term
  Disability
• Long-Term Disability
• Critical Illness/ Accident/ Hospital Indemnity/ Identity
  Theft Protection
• 401(k)

WHAT
you should know:

Our
success begins and ends with our people. We embrace
diverse perspectives and value unique human
experiences. WorldLink is an Equal Employment
Opportunity and Affirmative Action employer. All employment
at WorldLink is decided on the basis of
qualifications, merit, and business need. We endeavor
to continue our footprint as a diverse organization by
highlighting opportunities for all people. WorldLink
considers applicants for all positions without regard to
race, color, religion or belief, sex, (including pregnancy and
gender identity), age, national origin, political affiliation,
citizenship status, marital status, military/veteran status,
genetic information, sexual orientation, gender identity,
physical or mental disability or any other characteristic
protected by applicable laws. People with disabilities who need
assistance with any part of the application process should
contact us.

This
job description is designed to cover the main responsibilities
and duties of the role but is not designed to be a
comprehensive list of all.

Salary/Pay Range: $60.00-$93.00/hr (Depending on experience)