Senior AI/ML + Distributed Systems Engineer Required (Enterprise Build – $45,000 Fixed Price)

via Freelancer ·

Budget / Salary£750–1,500
TypeFreelance project
LocationRemote
Posted3 weeks ago
Senior AI/ML + Distributed Systems Engineer Required (Enterprise Build – $45,000 Fixed Price)

Project: AI Financial Intelligence & Risk Monitoring Platform

We are hiring a highly experienced engineer or engineering team to architect, build, deploy, and operationalize a production-grade AI Financial Intelligence & Risk Monitoring Platform.

This is not a prototype.
This is not a simulation.

This must be a fully scalable, real-time, enterprise-grade system capable of operating under production conditions.

⸻

Project Overview

The platform must:

* Process high-volume financial data streams in real time
* Detect anomalies using AI-driven models (not rule-based systems)
* Generate actionable risk intelligence
* Operate under strict performance, latency, and scalability benchmarks

Mock pipelines, placeholder logic, or simulated outputs will be treated as non-delivery.

⸻

Budget & Payment Structure – $45,000 Fixed

$40,000 – Advance Payment (Testing Phase Funding)

* Paid upfront upon project commencement
* Intended to fund development, infrastructure, and execution

Important:

* This payment does not constitute delivery, acceptance, or completion
* It does not waive any performance, scope, or deployment requirements
* It does not limit the Client’s rights in the event of non-delivery or breach

⸻

$5,000 – Final Payment

* Payable only upon:
* Full production deployment
* All systems operational and accessible
* All performance benchmarks achieved
* Transfer of:
* Source code
* Models
* Infrastructure access
* Documentation

Failure to meet these conditions voids entitlement to the final payment.

⸻

Scope of Work (Mandatory Deliverables)

Failure to deliver any core component constitutes non-delivery.

Data Ingestion & Processing

* Distributed ingestion pipeline (Kafka + Spark Streaming)
* High-throughput real-time data handling
* Data validation and preprocessing pipelines

Feature Engineering

* Feature store implementation
* Real-time and batch feature pipelines

AI & Risk Intelligence

* Hybrid anomaly detection (statistical + LSTM models)
* Ensemble-based risk scoring engine
* Real-time inference capability

Rule-only systems, hardcoded logic, or simulated outputs do not qualify.

⸻

Explainability Layer

* SHAP (or equivalent)
* Transparent and interpretable model outputs

⸻

Backend & API

* FastAPI-based architecture
* Secure APIs (OAuth2 / JWT)
* Scalable, modular backend design

⸻

Frontend Dashboard

* React-based analytics dashboard
* Real-time data visualization
* Full integration with backend services

⸻

Infrastructure & Deployment

* Kubernetes-based deployment
* CI/CD pipelines
* Monitoring stack (Prometheus, Grafana)
* Staged rollout strategy

Local-only or non-scalable deployments do not qualify.

⸻

Testing & Validation

* Stress testing under load
* Production-readiness verification

⸻

Performance Requirements (Mandatory)

The platform must meet all of the following benchmarks:

* ≥ 50,000 events/sec ingestion throughput
* ≤ 2 seconds ingestion latency
* ≤ 50 ms feature retrieval latency
* ≥ 90% anomaly detection precision
* ≤ 80 ms scoring latency
* ≤ 400 ms API response time
* ≤ 1.5 seconds dashboard load time

Failure to meet these metrics constitutes non-delivery.

⸻

Service Reliability Requirements

* Target uptime: 99.5% monthly availability

Exclusions include scheduled maintenance, force majeure, external infrastructure failure, and unauthorized usage.

Support Expectations

Working hours: 09:00–18:00 GMT/BST

Response and resolution:

* Critical: 4-hour response / 24-hour resolution
* Major: 8-hour response / 48-hour resolution
* Minor: 1 business day response / 5 business days resolution

⸻

Delivery & Acceptance Standard

Delivery is complete only when:

* Platform is fully deployed in production
* All scope items are fully functional
* AI models produce real, verifiable outputs
* Performance benchmarks are achieved
* Monitoring and CI/CD systems are operational
* Documentation is delivered
* Full source code, credentials, and infrastructure access are transferred

Anything less constitutes non-delivery.

⸻

Data, Security & Compliance

The Contractor must implement commercially reasonable safeguards aligned with:

* ISO 27001
* SOC 2 (Type I / II)
* PCI (where applicable)

All work must comply with applicable data protection laws, including GDPR where relevant.

The Contractor may use anonymized, aggregated data where legally permitted.

⸻

Intellectual Property

Upon final payment:

* All deliverables, including source code, models, and documentation, become the property of the Client

The Contractor retains ownership of:

* Internal tooling
* Deployment frameworks
* Generic infrastructure components

The Client retains full ownership of all data and datasets.

⸻

Confidentiality

Both parties agree to maintain strict confidentiality over:

* System architecture
* Pipelines and models
* Data and integrations

This obligation survives termination.

⸻

Refund Rights (Material Breach)

Failure to deliver a complete, production-ready system constitutes material breach.

This includes:

* Missed delivery obligations
* Non-functional system
* Failure to meet performance benchmarks
* Failure to deploy to production

The Client reserves the right to terminate and pursue recovery of payments subject to applicable terms and governing law.

⸻

Suspension Rights

The Contractor may suspend services if:

* Payments are overdue beyond 30 days
* Agreement breach occurs
* Unauthorized usage is detected
* Security risks arise

⸻

Limitation of Liability

Liability is limited as defined under applicable governing terms.

Nothing excludes liability for:

* Death or personal injury due to negligence
* Fraud
* Non-excludable statutory obligations

⸻

Force Majeure

Neither party is liable for delays caused by events beyond reasonable control, including:

* Natural disasters
* War
* Infrastructure failures
* Pandemics

⸻

Communication Requirement

All communication, updates, approvals, and documentation must occur exclusively via Upwork messages.

Off-platform communication does not amend this Agreement.

⸻

Governing Law

This agreement is governed by the laws of England and Wales.

All disputes fall under the exclusive jurisdiction of the courts of England and Wales.

⸻

Strict No Partial Acceptance Clause

* No partial acceptance of work
* No payment for incomplete or partially functional systems
* “Substantial completion” or “near completion” does not qualify
* Completion of individual modules does not entitle proportional payment
* Milestones, testing, or feedback do not constitute acceptance

Acceptance occurs only upon full system completion.

⸻

Who Should Apply

Applicants must demonstrate:

* Proven experience building production-grade distributed systems
* Deep expertise in real-time data pipelines
* Experience deploying AI/ML systems at scale
* Strong command of Kafka, Spark, Kubernetes, FastAPI, and React

⸻

Application Requirements

Include the following:

1. Relevant production systems (not demos)
2. High-level architecture approach
3. Team structure (if applicable)
4. Estimated timeline

⸻

Final Note

This is a high-stakes, enterprise-grade build.

Failure to deliver a complete, production-ready system that meets all requirements will result in the project being treated as non-delivered.
data processing cloud computing machine learning (ml) spark kubernetes anomaly detection api development ci/cd fastapi distributed systems
Apply on Freelancer →

Project sourced from Freelancer.com. Applications happen directly on the original platform — we never collect your data.