Senior Machine Learning Engineer

CodeNinja Inc.; Lahore; On-site; PKR 1,339,200 - 2,008,800; Full time

Benefits offered by this job

Provident Fund

Gym Membership

Leaves as per company policy

Company-paid trips

Yearly increment

Health insurance (maternity covered)

Job summary

CodeNinja Inc. in Lahore is looking for a Senior Machine Learning Engineer (Lead) to architect and develop advanced time-series forecasting solutions. Ideal candidates will have 5-6 years of experience in machine learning with a strong focus on financial applications. This role requires deep technical expertise, with responsibilities ranging from data acquisition to production-ready ML pipelines.

Join a dynamic team to work on impactful forecasting problems and drive innovation in financial decision-making.

Qualifications

• 5-6 years of hands-on ML engineering experience focused on time-series forecasting.
• Proven experience in financial domain use cases such as FX forecasting and treasury operations.
• Strong Python proficiency including libraries like pandas and XGBoost.

Responsibilities

• Lead end-to-end development of time-series forecasting solutions.
• Develop and benchmark statistical models and ML approaches.
• Collaborate with engineering teams to deploy solutions in cloud environments.

Skills

Machine Learning

Time-Series Forecasting

Financial Risk Modelling

Python (pandas, NumPy, scikit-learn)

Communication Skills

Education

Bachelor’s or Master’s in Computer Science, Data Science, Statistics

Tools

AWS SageMaker

Azure ML

GCP AI

Job description

About CodeNinja

CodeNinja is a full‑stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence‑driven systems for mission‑critical workflows. We specialise in deploying AI into real operations—combining strong engineering fundamentals with AI‑native delivery to create measurable value, resilience, and long‑term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centres, enabling teams to co‑engineer scalable platforms across regions and time zones.

Role Overview

We are seeking a Senior Machine Learning Engineer (Lead) with 5‑6 years of experience to architect, develop, and lead advanced time‑series forecasting solutions for high‑impact financial use cases. This role requires deep technical expertise in machine learning, strong financial domain knowledge, and the ability to translate research‑driven models into production‑grade systems within mission‑critical environments.

You will play a pivotal role in building robust, interpretable, and scalable forecasting models supporting financial risk management, FX exposure, treasury planning, and multi‑entity forecasting.

Key Responsibilities

• Lead end‑to‑end development of time‑series forecasting solutions—from data acquisition and feature engineering to deployment and monitoring.
• Architect scalable ML pipelines tailored for financial forecasting use cases.
• Develop and benchmark classical statistical models (ARIMA, SARIMA, ETS) alongside ML approaches (XGBoost, Gradient Boosting, Prophet, etc.).
• Design advanced time‑series features including lag structures, rolling statistics, seasonal/trend decomposition, Fourier terms, regime indicators, and exogenous variable integration.
• Implement time‑aware cross‑validation strategies and Bayesian hyperparameter optimisation.
• Conduct rigorous back‑testing aligned with financial validation methodologies.
• Build forecasting models for FX exposure, treasury cash flow prediction, inter‑company netting optimisation, financial risk modelling, and multi‑currency and multi‑entity forecasting.
• Quantify model uncertainty and incorporate confidence intervals.
• Perform anomaly detection and outlier analysis on financial time‑series datasets.
• Ensure models align with financial reporting cycles, treasury constraints, and accounting standards.
• Design reproducible ML workflows and production‑ready pipelines, including model versioning, monitoring, drift detection, and automated retraining strategies.
• Collaborate with engineering teams to deploy solutions in cloud environments.
• Build business‑facing dashboards (Streamlit, Tableau, Power BI).
• Ensure model governance, documentation, auditability standards are maintained.
• Translate complex technical insights into actionable business narratives.
• Partner with Finance, Treasury, Risk, and Executive stakeholders.
• Mentor junior ML engineers and establish best practices in feature engineering, validation, and interpretability.
• Promote technical excellence and maintain high code‑quality standards.

Requirements

• 5‑6 years of hands‑on ML engineering experience focused on time‑series forecasting.
• Proven experience in financial domain use cases such as FX forecasting, treasury operations, and financial risk modelling.
• Deep understanding of time‑series feature engineering (lags, rolling aggregates, decomposition, exogenous drivers).
• Experience with classical forecasting models (ARIMA, SARIMA, Exponential Smoothing).
• Strong Python proficiency (pandas, NumPy, scikit‑learn, XGBoost, Prophet).
• Expertise in time‑aware cross‑validation, Bayesian hyperparameter optimisation, and model interpretability techniques (SHAP, LIME).
• Strong understanding of evaluation metrics (MAPE, MAE, RMSE) and statistical validation methods.
• Experience building data pipelines and working in research environments (e.g., Jupyter).
• Strong communication skills for both technical and finance stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.

Preferred / Advanced Skills

• Experience in multi‑entity and multi‑currency financial forecasting environments.
• Familiarity with cloud ML platforms (AWS SageMaker, Azure ML, GCP AI).
• Experience implementing CI/CD and MLOps frameworks.
• Exposure to probabilistic forecasting and Bayesian modelling approaches.
• Knowledge of financial regulations, treasury workflows, and corporate finance processes.

Why Join Us

• Work on high‑impact financial forecasting problems that directly influence strategic decision‑making.
• Lead cutting‑edge machine learning initiatives in a mission‑critical environment.
• Collaborate with cross‑functional leadership across finance, risk, and engineering.
• Opportunity to architect scalable ML systems from research to enterprise production.
• Be part of a culture that values innovation, ownership, and technical excellence.

Equal Opportunity Statement

We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply.

Benefits

• Provident Fund
• Gym Membership
• Leaves as per company policy
• Company‑paid trips
• Easy loan facility for employees
• Yearly increment
• Maternity benefits (Leaves & WFH)
• Health insurance (maternity covered) – includes spouse and parents (till age 80)