Experience : 1.00 + years
Salary : INR 1800000-2200000 / year (based on experience)
Expected Notice Period : 15 Days
Shift : (GMT+05 : 30) Asia / Kolkata (IST)
Opportunity Type : Remote
Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by : Zero to 1)
- Note : This is a requirement for one of Uplers' client - Zero to 1)
What do you need for this opportunity
Must have skills required :
graph features (PPR, Graph / GraphRAG : Neo4j, Jaccard) for constrained recommendations, Re-rankers : cross-encoders, reranking with transformers,
Languages : Python 3.10+, Classical ML : scikit-learn, cross-val, Data : pandas, Delta Lake (S3), Feature Engineering, LightGBM / XGBoost, model selection, NumPy, Parquet; Spark / EMR Serverless or Glue (nice), Pyarrow, strong SQLZero to 1 is Looking for :
Job Description Context for candidates
RecSys v1 : Embedding-based candidate gen from Milvus + L2R (LightGBM) re-ranker with business rules
RAG quality : retrieval metrics, hard-negative mining, prompt & grounding eval suitesAgent signals : convert agent outputs (rationales / paths) to features; add auditability & explanationsData contracts : Bronze / Silver / Gold tables on Delta with provenance columnsMust-have keywords (for resume screening)
Languages : Python 3.10+, strong SQLData : pandas, NumPy, PyArrow, Delta Lake (S3), Parquet; Spark / EMR Serverless or Glue (nice)Classical ML : scikit-learn, LightGBM / XGBoost, feature engineering, model selection, cross-valRecommenders : candidate generation (embeddings / similarity), learning-to-rank, click models, cold-start strategiesLLMs & Agents : prompt design, tool / function calling, RAG, retrieval evaluation, LangChain / LangGraphEmbeddings & Vector Search : text embedding models, Milvus / Zilliz (IVF / HNSW),FAISS basicsEvaluation : NDCG@K, MRR, MAP, precision / recall, AUC; offline / online A / B test design, guardrailsMLOps / Experimentation : MLflow or Weights & Biases, Docker, reproducible notebooks → scripts, data / label versioningAPIs : package a model via FastAPI (basic), pydantic, async I / O familiaritySecurity / tenancy : PII handling, anonymization, KMS / IAM basicsNice-to-have
Graph / GraphRAG : Neo4j, graph features (PPR, Jaccard) for constrained recommendationsRe-rankers : cross-encoders, reranking with transformersCausal / Experimentation : CUPED, diff-in-diff, power analysisBatch & Orchestration : Step Functions / EventBridge, Airbyte / dbtObservability : data quality (Great Expectations), tracing / metrics in CloudWatchBedrock / OpenAI : model selection, cost / latency tradeoffs, prompt safetyDay-to-day toolset
Python (poetry / uv), Jupyter / VS Code, GitHub Actions CIData : Athena / Glue Catalog, S3 + Delta, SQL on Postgres / Aurora for app joinsVector : Milvus (HNSW / IVF), embedding pipelinesServing : FastAPI endpoints for ranking / feature-service; SQS / Step Functions for batch jobsExperimentation : MLflow model registry, W&B dashboards, AB testing framework hooksHow to apply for this opportunity
Step 1 : Click On Apply! And Register or Login on our portal.Step 2 : Complete the Screening Form & Upload updated ResumeStep 3 : Increase your chances to get shortlisted & meet the client for the Interview!About Uplers :
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note : There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
Skills Required
S3, model selection , Sql, Numpy, Pandas, Docker, XGBoost, Spark, FastAPI
