Senior AI/ML Engineer

Devsinc

full-time

Posted on: 9/22/2025

Origin: • 🇵🇰 Pakistan

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Senior

AWSAzureCloudDjangoDockerEC2FlaskGoogle Cloud PlatformKerasLinuxMicroservicesNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Develop and maintain scalable, secure AI and machine learning applications using Python and ML frameworks (e.g., TensorFlow, PyTorch).
Design and implement machine learning models and algorithms to support AI-driven client applications, focusing on user interface interactions and AI-driven features.
Integrate third-party AI/ML APIs and services into existing web applications.
Deploy Transformer-based models into production and manage model lifecycle in cloud environments.
Lead and participate in NLP and computer vision model development and provide constructive feedback to team members.
Promote a data-driven, machine learning approach and consistently deliver AI enhancements.
Work with cloud platforms (AWS, Azure, GCP, Databricks), Spark, and related AI libraries; ensure security and scalability.
Collaborate with cross-functional teams to design innovative AI solutions and take personal responsibility for deliverables.

Active coder with proficiency in Python 3.x, strong Object-Oriented Programming (OOP) skills, and familiarity with modern Python features.
Proven experience in Natural Language Processing (NLP) and Computer Vision (CV).
In-depth knowledge of Python libraries: numpy, pandas, scikit-learn, TensorFlow, PyTorch, Keras, Transformers.
Competence working with cloud environments (AWS, Azure, GCP, Databricks) and Linux; experience with Lambda/Serverless, SQS, SNS, S3, EC2.
Experience deploying Transformer-based models into production.
Proficiency in Django or Flask is a plus.
Strong expertise in Git for source control, code review, and repository management.
Familiarity with software engineering principles and design patterns (Dependency Injection, SOLID, Service Containers, Providers).
Experience with containerization technologies like Docker.
Proficiency in building highly distributed, eventually consistent AI systems.
Familiarity with microservices architecture and message broker systems.
Expertise in machine learning testing methodologies: unit, integration, performance, and load testing.
Knowledge of data visualization, monitoring, and alerting concepts and tooling.
Excellent knowledge of Relational Databases, SQL, and ORM technologies such as SQLAlchemy.
Knowledge of LLMs, including fine-tuning and deployment integration with web applications.
Strong background in machine learning and deep learning frameworks; experience with Spark.