Real Time Inference

Real Time Inference Engineer Jobs

3 jobs found

1mo ago

Sr. Machine Learning Engineer, Pricing, Robotaxi

Tesla Palo Alto, CA

Palo Alto, CA

1mo ago Closed

$172k - $258k/yr Full time Artificial Intelligence Data Pipeline Data Processing

This position is no longer accepting applications (closed Oct 24, 2026).

Job Description

Tesla’s Robotaxi division is building real-time pricing capabilities that help align rider experience with operational revenue and cost efficiency. As a Sr. Machine Learning Engineer for Pricing, you will use first principles to design, train, and productionize models that translate trip context into trustworthy, dynamic fare quotes for a driverless fleet.

This onsite role is based in Palo Alto, CA and focuses on shipping low-latency pricing intelligence that can scale across markets.

What You’ll Do

Design, train, and productionize machine learning models for real-time Robotaxi pricing, including base fare, distance and time, demand, traffic, tolls, taxes, government fees, and location-specific surcharges
Build price-elasticity, conversion, and competitive-response models
Develop dynamic, contextual pricing with logical guardrails that protect rider trust and quote fairness
Productionize ML and optimization pipelines, including feature engineering, training, low-latency inference, experimentation, monitoring, and rollback
Analyze ride sessions, costs, and competitor prices to continuously improve the pricing stack, and support global expansion with market-specific fees and airport and event experiences
Partner with growth and profitability teams to help maintain economically scalable fleet operations

What You’ll Bring

A degree in Computer Science, Machine Learning, Operations Research, Economics, or a related field, or proof of exceptional skills in a related field, or equivalent experience
4+ years developing and deploying machine learning models and pricing or marketplace algorithms in large-scale production environments
Experience in rideshare, marketplace, or large-scale dynamic pricing (strongly preferred)
Proficiency in Python and at least one of Go, C++, Java, or Scala; experience building backend distributed systems and low-latency, user-facing services
Experience with deep learning, causal machine learning, and/or reinforcement learning for pricing or real-time decisioning
Experience with large-scale data systems, deep learning, and ML/RL for pricing and real-time decisioning
Strong experimentation instincts, first-principles economics, and high standards for optimal outcomes
Ability to solve open-ended, difficult technical problems with little guidance and collaborate effectively across product, finance, billing, and engineering

Technologies

Python
Go
C++
Java
Scala

Compensation

USD 172,000 - 258,000 per year (annual salary) plus cash and stock awards and benefits. Pay may vary based on individualized factors, including market location, job-related knowledge, skills, and experience. Total compensation may include other elements depending on the position offered.

Benefits

Medical plans with $0 payroll deduction
Family-building, fertility, adoption and surrogacy benefits
Dental (including orthodontic coverage) and vision plans with options and $0 paycheck contribution
Company paid HSA contribution when enrolled in the High-Deductible medical plan with HSA
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
Company paid Basic Life and AD&D
Short-term and long-term disability insurance (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions) and Paid Holidays
Back-up childcare and parenting support resources
Voluntary benefits including critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
Weight Loss and Tobacco Cessation Programs
Tesla Babies program
Commuter benefits
Employee discounts and perks program

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1mo ago

Software Engineer III, ML, TPU Efficiency, YouTube

YouTube Mountain View, CA

Mountain View, CA

1mo ago Closed

$147k - $210k/yr Full time Ai Accelerators Data Pipeline Data Processing

This position is no longer accepting applications (closed Oct 24, 2026).

Job Description

YouTube is hiring a Software Engineer III to improve the efficiency of the models that power the YouTube algorithm. This role focuses on reducing training and serving costs while increasing fleet utilization through work that spans ML workload profiling, algorithmic efficiency, and co-design between model implementation and TPU compiler aspects.

Work location: Mountain View, CA (onsite)

Compensation: $147,000 - $210,000 USD per year + 15% bonus target + equity + benefits

Responsibilities

Profile ML workloads to pinpoint compute and memory bandwidth bottlenecks, then optimize accelerator utilization to improve compute efficiency.
Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
Collaborate with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.

Requirements

Bachelor's degree or equivalent practical experience.
2 years of experience programming in C++ or Python.
2 years of experience with software design and architecture.
2 years of experience testing and launching software products.
Experience with ML model optimization.
Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., XLA).

Preferred Qualifications

Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.
Experience debugging correctness and performance issues across all levels of the ML software stack.
Experience with ML compilers and internals, including writing compiler optimization passes.
Familiarity with accelerator hardware architectures (TPUs/GPUs).

Technology Stack

C++, Python, TensorFlow, JAX, PyTorch, XLA, TPUs, GPUs

Interview process: In most instances, this position requires in-person interviews as part of the hiring process.

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1mo ago

Machine Learning Engineer

Liquid XR Los Angeles, CA

Los Angeles, CA

1mo ago Closed

Full time Ai Ml Artificial Intelligence Data Pipeline

This position is no longer accepting applications (closed Sep 29, 2026).

Job Description

Liquid XR is looking for a Machine Learning Engineer to help build advanced models that reveal meaningful signals from multimodal time-series data. The work centers on creating robust real-time algorithms that can handle noisy, high-frequency sensor inputs while fitting practical latency and compute constraints.

Role summary

In this position, you will design end-to-end machine learning solutions for sequential data, including model development, training strategy, evaluation, and productionization with cross-functional teams. The focus includes signal extraction, latent variable learning, and sensor fusion approaches that move beyond purely classical pipelines.

Responsibilities

Design and implement machine learning models for time-series and sequential data
Develop algorithms to extract structured signals and latent variables from noisy sensor inputs
Build and optimize real-time inference pipelines under latency and compute constraints
Apply multi-modal learning and sensor fusion techniques
Replace or augment classical signal processing pipelines with learned models
Design training strategies for windowed and streaming data
Design training strategies for weakly labeled or partially observed datasets
Design training strategies for multi-task learning setups
Evaluate models using both statistical metrics and application-driven performance criteria
Collaborate with cross-functional teams to bring models from research to production
Explore architectures including Temporal convolutional networks (TCNs)
Explore architectures including RNNs, LSTMs, and GRUs
Explore architectures including Transformer-based sequence models

Required qualifications

Strong experience with machine learning for time-series data
Experience with transfer learning and knowledge distillation techniques
Proficiency in Python and PyTorch (or similar frameworks)
Solid understanding of signal processing fundamentals, including filtering, noise, and frequency domain concepts
Experience working with real-world, noisy datasets
Experience building or deploying low-latency, real-time systems
Experience with sensor data (for example, IMUs)
Familiarity with sensor fusion methods such as Kalman filters and probabilistic models
Experience with multi-modal or multi-task learning
Exposure to embedded or edge deployment constraints
Background in applied domains involving physical systems or human data
BSc or MSc in quantitative fields such as computer science, engineering, physics, or applied math
Ability to reason about temporal structure, causality, and latency
Strong intuition for tradeoffs between modeling goals and deployment constraints
Comfort working with imperfect, real-world data
End-to-end ownership from modeling through validation to deployment
Proactive, collaborative, detail-oriented, adaptable, and resilient working style

Technologies

Python
PyTorch
RNNs
LSTMs
GRUs
Transformer-based sequence models
Temporal convolutional networks (TCNs)
Kalman filters

Education

BSc or MSc in quantitative fields

Location and employment

Los Angeles, CA (hybrid) or remote work
Full-time employee position

Compensation and benefits

Compensation commensurate with experience and competitive with the market
Employee stock option program
Health care benefits starting within 30 days of employment (currently gold PPO coverage with Blue Shield, plus dental and vision)
Open PTO company

Travel

Occasional domestic and international travel may be required

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Real Time Inference Engineer Jobs

Sr. Machine Learning Engineer, Pricing, Robotaxi

Software Engineer III, ML, TPU Efficiency, YouTube

Machine Learning Engineer

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