AI Engineering
MLOps Engineer
If you like the kind of work a MLOps Engineer does, every challenge here gives you a chance to do that work on a real industry brief.
- CodeIntermediateNew
Ship a Lightweight ML Microservice for an EdTech Reading App
You receive 3 months of session telemetry (around 50M reading events, child-anonymized). Engineer features per session window, train a small classifier (logistic regression base…
- Feature Engineering
- Model Serving
- Containerization
Applied Machine Learning - CodeAdvancedNew
Detect Change Points in a Trading Platform's Latency Telemetry
You receive 90 days of per-millisecond latency telemetry across 12 services, plus an incident log of 14 known regressions and 22 known false-alarm-class events. Implement and tu…
- Change Point Detection
- Anomaly Detection
- Time Series Analysis
Time Series Analysis and Forecasting - CodeExpertNew
Cost-Optimize a 24/7 LLM API Cluster
Profile the current usage (24-hour trace, per-team breakdown). Pick a cost-optimization mix from: time-based autoscaling, spot/preemptible instances with graceful drain, smarter…
- Llm Serving
- Autoscaling
- Ray
ML Engineering and Production ML - CodeExpertNew
Auto-Tune a Distributed Training Cluster's Throughput
Pick a representative fine-tune job (an open 7B model on a public instruction dataset is fine). Define the search space: NCCL_ALGO, NCCL_PROTO, num_workers, prefetch_factor, gra…
- Distributed Training
- Hyperparameter Tuning
- Nccl
Machine Learning Systems Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- CodeAdvancedNew
Build a Canary Rollout for a Production Recommender
Pick a serving stack (Triton, Seldon Core, KServe, or BentoML). Implement two-model traffic splitting with a configurable percentage (start at 5%). Wire up online metric collect…
- Canary Deployment
- Kubernetes
- Ab Testing
ML Engineering and Production ML - CodeAdvancedNew
Design Prompt Versioning and Observability for a Coding Assistant
You will (1) design a prompt-registry data model (versions, owners, environments, change log) and implement it in Postgres + a small Python SDK, (2) instrument the assistant to …
- Prompt Versioning
- Observability
- Pii Scrubbing
LLM Application Development - CodeAdvancedNew
Automate Retraining with a Drift-Triggered MLflow Pipeline
Stand up the pipeline end to end with the team's existing stack (MLflow tracking + model registry, Airflow orchestration). Wire Evidently to compute weekly drift; when drift cro…
- Mlflow
- Airflow
- Data Drift Detection
ML Engineering and Production ML - CodeAdvancedNew
Containerized Model Inference on Kubernetes for a Fintech
You receive a pre-trained credit-risk model (a LightGBM model file) and a sample request payload. Containerize a FastAPI inference service, deploy to EKS or GKE (a single-zone c…
- Kubernetes
- Containerization
- Autoscaling
Cloud Computing for Data and ML - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- CodeAdvancedNew
Quantize a CNN for Battery-Powered Wildlife Cameras at a Climate Nonprofit
You receive an FP32 CNN (MobileNetV2 fine-tuned to 22 species, around 13 MB) and a hold-out test set of 4,000 images. Quantize to int8 (post-training quantization first, then qu…
- Quantization
- Qat
- Edge Deployment
Deep Learning - CodeExpertNew
Build an MLOps Platform Slice for a Fintech Risk Team
Across a 5-person team, ship (1) experiment tracking integrated into a sample model training job; (2) a model registry that promotes-by-tag; (3) a training pipeline orchestrated…
- Mlops Design
- Experiment Tracking
- Model Registry
AI Software Engineering Group Project
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Industry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.
Skills and disciplines shown on this page are derived from the Ewance challenge catalogue. When the median annual salary is available for this role via Adzuna, it will be shown above with the sample size and country.