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As an MLOps Engineer, you will work closely with researchers to optimize models, help shape the data they need for training, and instrument the system to measure and improve model performance. Working in close partnership with the Lead Infrastructure Engineer and Research Leads, you will translate requirements into durable operational processes and ensure the fleet operates effectively.
You will report to the Head of Data & Infrastructure.
Responsibilities:
- You will optimize how our models train and serve.
- You will build the streaming data path from lake to GPU.
- You will make our data formats a deliberate choice.
- You will instrument all of it including Per-job GPU utilization, queue depth and job success rate, cost per experiment, data-loader stall time, and serving latency percentiles.
- You will land the training and experiment telemetry into one place researchers and planners trust.
Qualifications:
- 8+ years of engineering experience
- 4+ years building and operating ML systems in production
- Expertise in Python
- Comfort reading and modifying framework-level code - PyTorch, and an inference server such as vLLM, SGLang or TensorRT-LLM
- Demonstrated model or inference optimization work
- Hands-on experience with distributed data processing for ML (including Ray, Spark, or equivalent) and columnar and ML-native formats (such as Parquet, Arrow, Lance, or similar)
- Practical observability skills including Prometheus, Grafana, or equivalent
- Working knowledge of AWS compute and storage as they apply to ML workloads - EC2 GPU instances, S3 and its performance tiers, EKS
- Experience with containerization and CI/CD for ML artifacts and a reproducibility instinct
This is a hybrid role, onsite three days a week, in Redwood City, Montreal, or Vancouver.
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Pay Transparency - North AmericaCOMPENSATION AND BENEFITS The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).
PAY RANGES* British Columbia (depending on location e.g. Vancouver vs. Victoria) *$141,400 - $204,400 CAD
* California (depending on location e.g. Los Angeles vs. San Francisco) *$165,000 - $256,000 USD
Pay is just one part of the overall compensation at EA.
In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.
For Canada, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.
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