Valiance Solutions - Lead Machine Learning Engineer

Description :

About Valiance :

Valiance Analytics is an AI-focused firm building real-world AI systems across demand forecasting, decision intelligence, GenAI applications, and agentic AI platforms. We work with global enterprises across the US and India, solving complex business problems using modern AI architectures.

Role Overview :

We are looking for a Senior Machine Learning Engineer (Tech Lead) to join our Data Science & Machine Learning team. The team collaborates closely with Sales, Product, and Engineering to design and implement next-generation retail solutions. You will play a key role in architecting and scaling a real-time ML platform that processes millions of retail items and generates billions of predictions daily.

Key Responsibilities :

1. ML Platform Architecture & Engineering :

- Translate abstract architecture into concrete technical designs

- Identify inefficiencies in cost and reliability; propose optimized solutions

- Research and evaluate open source/custom technologies

- Build and extend microservices in a secure, multi-tenant architecture

- Implement scalable, resilient, event-driven systems

2. ML DevOps & Operations :

- Implement DevOps best practices across ML systems

- Work closely with DevOps and Support teams

- Set up monitoring, logging, and alerting frameworks

- Ensure reliability, scalability, and high availability of ML services

3. Collaboration with Data Science Teams :

- Apply strong software engineering principles to ML model building and serving

- Build robust, production-ready pipelines for training and inference

- Support deployment of deep learning and interpretable ML models

Technical Environment :

- Programming : Python 3.x

- Cloud : Google Cloud Platform (GCP)

- Architecture : Scalable, resilient, reactive, event-driven microservices

- Technologies : Kubernetes, Kafka, Pub/Sub, BigQuery, Apache Beam, DataFlow, Kubeflow

- ML Frameworks : Keras, TensorFlow

- Web Frameworks : Flask / FastAPI

- Databases : Postgres, BigQuery, Cassandra, HBase, Redis

- Big Data : Hadoop, Spark

Required Qualifications :

- Bachelors degree in computer science (masters preferred)

- 6+ years of software engineering experience in production environments

- 3+ years of strong Python experience with solid OOP & design patterns knowledge

- 2+ years building REST APIs

- Hands-on experience with Kubernetes and containerized environments

- 2+ years of cloud experience (GCP preferred)

- 2+ years working with Kafka and cloud integrations

- 3+ years of Linux scripting

- Experience with SQL databases (Postgres, BigQuery preferred)

- Experience with NoSQL (Cassandra, HBase, Redis)

- CI/CD, GitHub Actions, automated unit & integration testing

- Exposure to streaming frameworks (Beam / Flink / DataFlow / Airflow)

- Strong understanding of data structures and algorithms

Good to Have :

- Experience with Pandas, NumPy, sklearn, Keras, TensorFlow

- Familiarity with Kubeflow and ML lifecycle management

- Experience building large-scale, real-time ML systems