Senior Software Engineer - Artificial Intelligence at Devsinc

Lahore, Punjab, Pakistan -

Full Time

Start Date

Immediate

Expiry Date

22 Mar, 26

Salary

0.0

Posted On

22 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, APIs, Microservices, MLOps, Python, PyTorch, TensorFlow, Cloud Platforms, Kubernetes, Data Engineering, Model Optimization, Collaboration

Industry

IT Services and IT Consulting

Description

Devsinc is seeking a highly experienced Senior AI Engineer with 3+ years of professional AI/ML experience to design, build, and deploy advanced AI systems in production environments. The ideal candidate brings strong software engineering fundamentals, deep expertise in machine learning and large language models (LLMs), and proven experience delivering scalable, real-world AI solutions. This role demands architectural ownership, technical leadership, and the ability to guide cross-functional teams through complex, end-to-end AI initiatives, from concept to deployment. Responsibilities Lead end-to-end development and delivery of AI initiatives, from concept to production deployment. Design, develop, and optimize AI/ML models including deep learning, NLP, computer vision, LLMs, and embedding-based systems. Build scalable pipelines for training, fine-tuning, evaluation, deployment, and continuous optimization. Develop production-ready inference services, APIs, and microservices with a strong focus on performance, reliability, and cost efficiency. Implement and manage MLOps workflows using tools such as SageMaker, MLflow, Vertex AI, W&B, Docker, and Kubernetes. Apply advanced model optimization techniques including quantization, distillation, batching, and GPU/TPU acceleration. Conduct experiments, research emerging AI techniques (LLMs, RAG, multimodal AI, vector search), and apply findings to real-world use cases. Collaborate with Data Engineering, Product, DevOps, and Business teams to deliver AI-driven features. Mentor junior and mid-level engineers, promoting best practices in AI and software engineering. Participate in system architecture design, CI/CD implementation, monitoring, and lifecycle management of AI systems. Ensure high standards of code quality, documentation, security, and compliance throughout the AI development lifecycle. Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. 3+ years of professional experience in AI/ML engineering roles, with Strong communication, collaboration, and leadership skills. Strong proficiency in Python and hands-on experience with PyTorch and/or TensorFlow. Proven experience deploying AI models in production at scale (APIs, microservices, real-time pipelines). Solid understanding of ML algorithms, feature engineering, dataset preparation, model evaluation, and optimization. Hands-on Experience with cloud platforms (AWS/GCP) and container orchestration (Kubernetes). Experience with distributed systems, GPU acceleration, and parallel computing. Hands-on experience with LLMs, RAG pipelines, vector databases, fine-tuning techniques (LoRA, QLoRA, PEFT), and building AI agents, workflow orchestration systems, or multimodal AI solutions. Strong understanding of data engineering concepts, real-time/streaming architectures, Kafka, Spark, ML infrastructure, along with model security, responsible AI, compliance, and risk mitigation. Proficiency with version control systems and CI/CD pipelines. Collaborative – works effectively with cross-functional teams. Team Player – mentors peers and contributes to collective success. Leadership-Oriented – capable of guiding teams and owning technical direction. Growth Minded – eager to learn and adapt to emerging AI technologies. Adaptable – thrives in fast-paced, dynamic environments. Customer-Centric – focused on building AI solutions that deliver real business value.

Responsibilities

Lead the development and delivery of AI initiatives from concept to production deployment. Design and optimize AI/ML models and build scalable pipelines for training and deployment.