Senior ML Engineer: Active Learning & Data Labeling

Sense; Town of Cambridge; On-site; AUD 235,000 - 263,000; Full time

Benefits offered by this job

Health Plan

Retirement Plan

Life Insurance

Paid Time Off

Family Leave

Disability Insurance

Work From Home

Free Food & Snacks

Wellness Resources

Stock Option Plan

Job summary

Sense is seeking a Senior Machine Learning Engineer specializing in active learning to scale data operations and improve production models. The role is hands-on: you will write code, train models, and guide annotators to generate high‑quality labels efficiently.

You will own the ground truth plan, design active learning strategies, and collaborate with data engineers, product, and hardware teams to drive label quality and model performance.

Qualifications

• MS or PhD in CS, Electrical Engineering, Physics, Statistics, or related field, or equivalent experience.
• 5+ years of experience in data science or machine learning, including 2+ years building or managing labeled datasets for ML.
• Hands-on experience applying active learning to real data, including choosing a sampling strategy and measuring impact.
• Experience finding rare or hard examples in large datasets from model errors or uncertainty.
• Experience training deep learning models, with weak supervision or model-assisted labeling.
• Experience measuring label quality and fixing label errors.
• Experience with Python, SQL, and data pipelines.
• Track record of working with product, software, or hardware teams.

Responsibilities

• Design and run active learning to select homes, devices, and time periods to label next.
• Turn detections and field results into new ground truth; track model improvement after retraining.
• Find rare events and hard cases in home data and add them to labeling sets.
• Own the ground truth plan: data, quantity, and labeling order.
• Direct a team of annotators; set priorities, track throughput, and ensure data quality.
• Develop annotation tools to improve data collection and model support.
• Measure label quality with metrics, outlier detection, and human review.
• Coordinate with data engineers and ML ops to version labels and separate eval sets from training data.

Skills

Active learning

Machine learning

Data science

Collaboration

Model evaluation

Education

MS or PhD in CS/EE/Physics/Statistics or related field

Tools

Python

SQL

Data pipelines

Job description

Sense is seeking a Senior Machine Learning Engineer specializing in active learning to scale data operations and improve production models. The role is hands-on: you will write code, train models, and guide annotators to generate high‑quality labels efficiently.

You will own the ground truth plan, design active learning strategies, and collaborate with data engineers, product, and hardware teams to drive label quality and model performance.