AI / Machine Learning Engineer

VAM Systems

VAM Systems

Years of Experience: 7 10 years

Qualification

Bachelor's Degree in Computer Science / Engineering

Preferably BE Computer Science & Engineering

Professional Training Required:

Professional Qualification Required:

Professional Certifications Required:

Experience required:

Ability to build and deploy ML models using Python and relevant libraries. Understanding of supervised and unsupervised learning algorithms.

Experience with model evaluation and performance metrics.

Familiarity with AI use cases in banking (e.g., fraud detection, personalization) Knowledge of data preprocessing and feature engineering.

Ability to work with cloud-based ML platforms (e.g., Azure ML, AWS SageMaker). Understanding of MLOps and model lifecycle management.

Ability to communicate insights and build explainable AI models.

Machine Learning / Deep Learning.

Statistics and Finance knowledge.

Data Preprocessing & Feature Engineering.

Model Deployment & MLOps.

Statistical Analysis.

Cloud AI Platforms.

Explainable AI (XAI).

Business Problem Solving

Job Responsibility:

Design and develop machine learning models to support AI-driven banking solutions Collaborate with data engineers to access and prepare data for modeling Apply statistical and ML techniques to solve business problems (e.g., churn prediction, credit scoring) Evaluate model performance and optimize for accuracy, precision, and recall Deploy models into production using MLOps frameworks and CI/CD pipelines Ensure models are explainable, auditable, and compliant with regulatory standards Work with business stakeholders to identify AI opportunities and define success metrics Document model assumptions, data sources, and performance benchmarks.

Core AI / NLP Engineering

Python (PyTorch, TensorFlow, LangChain, Hugging Face, OpenAI API, Anthropic Claude, etc.)

LLM fine-tuning (LoRA, PEFT, prompt tuning)

Retrieval-Augmented Generation (RAG), vector databases (Pinecone, FAISS, Weaviate, Chroma)

Prompt engineering and orchestration (LangChain, LlamaIndex, Semantic Kernel, DSPy)

Knowledge of embeddings, tokenization, and transformer architecture

Cloud AI tools: AWS Bedrock, Azure OpenAI, Vertex AI, OpenSearch, ElasticSearch

Model evaluation: hallucination detection, grounding, and benchmarking (BLEU, ROUGE, TruthfulQA, etc.)

Software Engineering & Backend Integration

RESTful and GraphQL APIs, webhooks

Containerization and deployment (Docker, Kubernetes, CI/CD)

Authentication and user/session management

Data pipelines and microservices

Knowledge of frameworks like FastAPI, Flask, NestJS, or Express

Integration with enterprise data (SharePoint, Salesforce, SQL, internal APIs)

Agent Orchestration & Tooling

LangGraph, AutoGen, CrewAI, Flowise, or similar agent frameworks

Task-decomposition and reasoning chains

Function calling, tool use, and API chaining

Memory design (short-term vs long-term)

Context management and grounding strategies.

Conversational UX / Design

Conversation design frameworks (Google CCAI, Microsoft Bot Framework, Voiceflow, Botpress)

Flow design and intent management (Dialogflow, Rasa, Cognigy)

Tone, empathy, and personality design for AI personas

A/B testing dialogue variants and measuring user satisfaction.

Data & Infrastructure

Data pipelines (Airflow, dbt, Kafka)

Structured/unstructured data ingestion (PDFs, databases, APIs)

Feature store and model registry management (MLflow, Kubeflow)

Vector database deployment and optimization

Monitoring, logging, and drift detection.

Governance, Security & Compliance

Model explainability (SHAP, LIME)

Bias/fairness audits and data privacy

Compliance with GDPR, ISO 42001, NIST AI RMF, and local banking regulations

Secure prompt logging and audit trails.

Products & Strategy

Translating business problems into AI use cases

Roadmapping and budget planning

KPI design (accuracy, user satisfaction, automation ROI)

Vendor management (OpenAI, Anthropic, AWS, etc.)

Change management and user adoption

Joining time frame: (15 - 30 days)

The selected candidates shall join VAM Systems Bahrainand shall be deputed to one of the leading banks inBahrain.

Should yoube interested in this opportunity, please send your latest resume at the earliest at [HIDDEN TEXT]