Intermediate/Senior AI Engineer 30-month salary/year

Mô tả công việc

ABOUT THE ROLE

If you’re ready to jump into real- world AI that delivers tangible outcomes in Global eCommerce, Crossian is your start.
As an Intermediate or Senior AI Engineer, you’ll be designing and deploying production- grade AI systems that directly move revenue, shape product strategy, and unlock growth across Global markets. Your models should serve for billions of events, live traffic, and show up in Company- wide KPOs. Beside, from fine- tuning LLMs to crafting recommendation engines, from designing Retrieval- Augmented Generation (RAG) pipelines to launching scalable microservices, you’ll work in the core Business Enablement (BE) squad alongside Product, Tech, and Marketing in a fast- paced, Agile playground where experimentation, ownership, and impact rule the day.

Model Development & Innovation

Build, train, and tune ML models for recommendations, propensity scoring, fraud detection, and demand forecasting.
Fine- tune and evaluate LLMs (GPT, Llama 3, Claude, etc.) for RAG pipelines, chatbots, and content- generation features.
Prototype quickly, run offline/online experiments, and iterate based on precision, recall, CTR, and business lift.

MLOps & Productionisation

Package models into scalable micro- services with Docker/Kubernetes, SageMaker, Vertex AI, or on- prem GPU clusters.
Implement monitoring for drift, latency, and cost, owning the full model lifecycle from commit to sunset.
Automate training, CI/CD, and rollout using GitLab CI, Terraform, and blue/green or canary deployments.

Data Engineering & Feature Platforms

Design vector- database schemas (OpenSearch, Pinecone, Chroma) and retrieval logic for RAG- based solutions.
Partner with Data Engineering to define feature contracts, real- time pipelines (Kafka, Kinesis), and data- quality checks.

Experimentation & Evaluation

Design online A/B and interleaving tests to measure incremental lift and guard- rail metrics.
Publish clear experiment readouts that influence product roadmaps and marketing budgets.

Cross- Functional Collaboration & Mentorship

Mentor junior engineers and drive best practices in coding standards, documentation, and peer review.
Embed in product squads, translating business problems into model specs and success metrics.

Yêu cầu công việc

Essential Qualifications & Skills

Bachelor’s degree in Computer Science, Data Science, Electrical Engineering, Statistics, or related field (Master’s is a plus).
Experience:
Intermediate: 3+ years of ML engineering.
Senior: 5+ years of ML / AI experience deploying models at scale (e- commerce, ad- tech, fintech, etc.).
Technical Proficiency:
Expert Python skills with ML frameworks (e.g., PyTorch, TensorFlow, LangChain).
Familiarity with Infrastructure- as- Code (e.g., Terraform).
Hands- on experience with cloud ML platforms (e.g., AWS SageMaker, Google Vertex AI, Azure ML) and container orchestration (e.g., Kubernetes).
Advanced SQL and experience with distributed data processing (e.g., Spark, Dask).
Analytical Rigor: Comfortable with statistical testing, causal inference, and experiment design.
Strong software engineering skills, including Git, REST/gRPC APIs, and design patterns.
Language: Professional English proficiency (written and spoken)
Deep knowledge of recommender systems, classification/regression, NLP, and evaluation metrics (e.g., AUC, F1, NDCG).
Agile DNA: Track record of working in Scrum/Kanban teams and iterative delivery.
Communication: Ability to translate model outputs into plain- English recommendations for non- technical stakeholders.
Preferred (Not Required)
Experience building large- scale recommender systems (e.g., deep retrieval, Reinforcement Learning- based ranking).
Contributions to open- source ML/AI projects, published papers, or patents.
Familiarity with knowledge graphs or graph neural networks.
Knowledge of GenAI security practices (e.g., prompt- injection mitigation, compliance frameworks).
Exposure to CUDA optimization, on- device inference, or streaming inference frameworks (e.g., Flink, Ray Serve).

High- Impact Shipping: Your models serve live traffic, influence eight- digit revenue decisions, and feature in company- wide OKRs.
Rapid Career Growth: Clear promotion pathways, GPU credits for side projects, conference budget, and mentorship from senior ML leaders.
Competitive Compensation: Base salary plus performance bonuses worth up to 30 months of pay per year.
Ownership Culture: You own your code, experiments, and roadmap and have every opportunity to showcase your capabilities.
Massive AI Playground: Billions of daily events across text, clickstream, images, and payments ready for experimentation.

Cập nhật gần nhất lúc: 2025-08-29 00:15:03