Mid level Machine Learning Engineer

Position: Mid Level ML Engineer

Experience: 3 to 5 years

Education: BSCS in computer science

What You’ll Do

• Design, develop, and deploy scalable machine learning models and AI-driven solutions.
• Lead the development and automation of ML pipelines, ensuring efficiency and scalability from model training to inference.
• Optimize ML workflows, automating redundant tasks and streamlining deployment.
• Implement MLOps best practices, including model monitoring, versioning, and CI/CD for machine learning.
• Build and maintain cloud-based ML infrastructure, leveraging containerized platforms (Docker, AWS, Azure).
• Collaborate with cross-functional teams (data scientists, engineers, and business leaders) to align ML initiatives with business goals.
• Mentor junior engineers and support their professional growth.
• Stay up to date with AI advancements, researching and applying state-of-the-art ML techniques.

Who You Are

• 4+ years of experience in AI/ML development, with a strong focus on ML engineering and infrastructure.
• Expertise in deep learning frameworks, including Computer Vision (e.g. YOLO, Open-CV), NLP models (e.g., BERT, GPT), LLMs and traditional ML techniques.
• Proficiency in Python and ML libraries such as Pandas, Numpy, Scikit-learn, TensorFlow, and PyTorch.
• Strong understanding of data structures, algorithms, and scalable system design.
• Hands-on experience with containerized platforms (Docker, Kubernetes) and cloud environments (AWS, GCP, Azure).
• Experience with MLOps tools such as Weights & Biases, MLflow, LangChain, LangSmith, and similar platforms.
• Experience optimizing ML inference pipelines for performance and cost efficiency.

Nice-to-Have

• Experience with building and maintaining Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases and retrieval techniques to enhance LLM-powered applications.
• Familiarity with distributed computing and big data technologies.
• Contributions to open-source ML projects or research publications.

Job Type: Full-time

Application Question(s):

• Do you have an Experience with building and maintaining Retrieval-Augmented Generation (RAG) pipelines
• How many years of experience in deep learning frameworks, including Computer Vision (e.g. YOLO, Open-CV), NLP models (e.g., BERT, GPT), LLMs and traditional ML techniques.
• How many years of Experience in Python?
• How many years of experience in ML libraries such as Pandas, Numpy, Scikit-learn, TensorFlow, and PyTorch
• Do you have Hands-on experience with containerized platforms (Docker, Kubernetes)
• How many years of experience in cloud environments (AWS, GCP, Azure)
• Do you have an Experience with MLOps tools such as Weights & Biases, MLflow, LangChain, LangSmith, and similar platforms.
• Current Salary
• Expected Salary
• Notice Period?

Education:

• Bachelor's (Required)

Experience:

• ML Engineer: 5 years (Required)

Work Location: Remote