Machine Learning Engineer

Role & rJob Title: Senior Machine Learning Engineer Anomaly Detection & Time Series Forecasting Location: Bangalore Department: Engineering – AI/ML

Job Overview:

Resolve Tech Solutions is seeking an experienced Senior Machine Learning Engineer to drive the development of AI-driven anomaly detection, time series forecasting, and predictive analytics models for our next-generation observability platform. This role will focus on designing, building, and deploying ML models that provide real-time insights, predictive alerts, and intelligent recommendations powered by LLMs. As a key individual contributor, you will work on solving complex challenges in large-scale cloud environments while collaborating with cross-functional teams.

Key Responsibilities:

Develop Advanced ML Models: Design and implement machine learning models for anomaly detection, time series forecasting, and predictive analytics, ensuring high accuracy and scalability.

Anomaly Detection & Root Cause Analysis: Build robust models to detect abnormal patterns in metric data, leveraging statistical methods, deep learning, and AI-driven techniques.

Time Series Forecasting: Implement predictive models to forecast metric trends, proactively identifying threshold breaches and alerting users.

LLM-Driven Insights: Utilize Large Language Models (LLMs) to analyze historical incidents, correlate anomalies, and provide recommendations by integrating with ITSM platforms like ServiceNow.

Cloud & Big Data Integration: Work with large-scale data pipelines, integrating ML models with cloud platforms such as AWS, Azure, and GCP.

Feature Engineering & Data Processing: Design and optimize feature extraction and data preprocessing pipelines for real-time and batch processing.

Model Deployment & Optimization: Deploy ML models in production environments using MLOps best practices, ensuring efficiency, scalability, and reliability.

Performance Monitoring & Continuous Improvement: Establish key performance metrics, monitor model drift, and implement retraining mechanisms for continuous model improvement.

Collaboration & Knowledge Sharing: Work closely with product managers, data engineers, and DevOps teams to align ML solutions with business objectives and platform goals.

Requirements:

Experience: 5+ years of hands-on experience in machine learning, with a strong focus on anomaly detection, time series forecasting, and deep learning.

ML & AI Expertise: Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, and XGBoost.

Anomaly Detection: Experience with statistical techniques, autoencoders, GANs, or isolation forests for anomaly detection in time series data.

Time Series Forecasting: Strong background in models such as ARIMA, Prophet, LSTMs, or Transformers for predictive analytics.

LLMs & NLP: Hands-on experience in fine-tuning and integrating LLMs for intelligent insights and automated issue resolution.

Cloud & Data Engineering: Familiarity with cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI) and distributed computing frameworks like Spark.

MLOps & Deployment: Experience with CI/CD pipelines, Docker, Kubernetes, and model monitoring in production.

Problem-Solving & Analytical Skills: Ability to analyze large datasets, derive insights, and build scalable ML solutions for enterprise applications.

Communication & Collaboration: Strong verbal and written communication skills, with the ability to explain ML concepts to non-technical stakeholders.

Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.

Preferred Qualifications:

Experience with AIOps, observability, or IT operations analytics.

Hands-on experience with reinforcement learning or graph neural networks.

Familiarity with Apache Kafka, Flink, or other real-time data processing frameworks.

Contributions to open-source ML projects or research publications in anomaly detection and time series analysis.

Why Join Us?

Opportunity to work on cutting-edge AI/ML solutions for enterprise observability.

Collaborative and innovative work environment with top AI/ML talent.

Competitive salary, benefits, and career growth opportunities.

Exposure to large-scale, cloud-native, and AI-driven technologies.

If you are passionate about AI-driven anomaly detection, time series forecasting, and leveraging LLMs for real-world enterprise solutions, we'd love to hear from youesponsibilities

Preferred candidate profile