Machine Learning - ML Engineer (Hanoi) at TechX Corporation

Hanoi, , Vietnam -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Anomaly Detection, Forecasting Models, Time-Series Analysis, Python, MLOps, Data Preprocessing, Model Evaluation, Deep Learning, Cloud Environments, Operational Data, Correlation Logic, Root-Cause Indicators, Synthetic Data, Monitoring, Performance Tuning

Industry

IT Services and IT Consulting

Description

Company Overview: At TechX, we are pioneers in delivering cutting-edge solutions that empower businesses to thrive in today’s digital landscape. With a strong focus on Cloud Transformation (AWS), Data Modernization, and Generative AI, we bring unparalleled expertise to drive innovation, efficiency, and growth for our clients. We specialize in banking and financial services, retail, manufacturing, and transportation, delivering impactful solutions that address industry-specific challenges and significant market shifts. Together, we’ll build a future where innovation knows no limits. Job Description: We are hiring Senior and Junior ML Engineers to work on Synaptix’s AIOps capabilities, focusing on anomaly detection, forecasting models, correlation logic, and root-cause indicators. You will work closely with senior ML engineers and MLOps to build, test, and operationalize machine learning pipelines that process large-scale time-series and operational data. This role is ideal for ML engineers who want to grow in time-series modeling, anomaly detection, and applied ML for real-world IT operations. Key Responsibilities: Core Model Development Design and implement anomaly detection and forecasting models (EWMA, Z-score, CUSUM, Seasonal Percentile, SARIMA). Experiment with LSTM, Transformers, or other deep learning architectures for time-series analysis. Develop correlation logic and root-cause indicators for AIOps insights. Data & Synthetic Modelling Build synthetic data modules to simulate operational scenarios and anomalies. Preprocess and analyze time-series datasets for modeling and evaluation. Pipeline & MLOps Collaboration Work with the MLOps team to operationalize ML models into production pipelines. Assist with model deployment, monitoring, and performance tuning. Document experiments, results, and model behaviors clearly. Key Requirements: >1 to 5+ years of experience in ML engineering or applied machine learning. Strong understanding of anomaly detection algorithms Proficiency in Python and ML frameworks Experience with model evaluation, metric design, and ML experimentation Familiarity with time-series libraries (statsmodels, Prophet, etc.). Knowledge of production ML (MLOps concepts, monitoring, pipelines). Understanding of IT Operations and AIOps data types (metrics/logs). Basic experience with cloud or containerized environments. What We Offer: Innovative Environment: A dynamic and collaborative work environment where innovation is encouraged. Professional Growth: Opportunities for professional growth and development through continuous learning and exposure to cutting-edge technologies. Competitive Package: Competitive salary and benefits package Impactful Work: The chance to work on cutting-edge projects with industry-leading clients, making a tangible impact on their business success. Apply now! Due to the high volume of applicants, only shortlisted candidates will be contacted. We apologize for this inconvenience!

Responsibilities

The role involves designing and implementing anomaly detection and forecasting models, as well as collaborating with the MLOps team to operationalize machine learning models. Engineers will also preprocess and analyze time-series datasets and document their experiments and results.