Job Title : ML Engineer

Internal Role level : Level 3/ 4

Overall Industry Experience : 5 to 7 years

Night Shift only - Customer support time - 8 am to 5 pm EST.

Job Overview

Business Hours” are defined to be from 8:00 AM until 5:00 PM in Eastern Standard

Time. Business Hours are applicable only on Business Days

We are seeking a highly motivated and experienced ML Engineer to join our growing

ML/GenAI team. In this role, you will play a key part in designing, developing,

fine-tuning, and productionalizing both classical ML applications and cutting-edge

GenAI solutions. As a senior member of the team, you will take ownership of projects,

collaborating with engineers and Customers to ensure successful project delivery.

Key Responsibilities

- End-to-End ML Development: Design, train, fine-tune, and operationalize robust

ML models for real-world customer applications.

- GenAI & LLM Implementation: Develop and optimize production-grade

Retrieval-Augmented Generation (RAG) systems. Design, evaluate, and iteratively

modify prompts to maximize LLM response accuracy.

- Data & Feature Engineering: Collaborate with teams to analyze, clean, and

preprocess datasets (handling outliers, imbalances, and distributions) and

transform raw data into high-quality features.

- Production & MLOps: Build and deploy scalable ML pipelines on GCP. Implement

robust monitoring strategies to track model performance, identify data drift,

and resolve issues in production environments.

- Collaboration & Ownership:



Act as a senior member on customer-facing projects,

translating client needs into secure, performant, and scalable architectures.

What We Are Looking For (Requirements)

- Experience:

Minimum 5 years of core Software Engineering experience building

secure, scalable, and performant applications.

Minimum 3 years of hands-on experience specifically designing, building,

and deploying ML applications in production.

- Technical Domain Expertise:

Strong foundational knowledge of Natural Language Processing (NLP),

Computer Vision, or other Deep Learning techniques.

Proven experience building and deploying RAG (Retrieval-Augmented

Generation) architectures and engineering prompts for LLMs.

- Tools & Frameworks:

Expertise in Python and standard data science libraries (NumPy, Pandas,

Scikit-learn).

Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost) and

GenAI orchestration tools (LangChain or similar).

- Cloud Infrastructure: Hands-on experience building pipelines on cloud platforms,

specifically Google Cloud Platform (GCP) and its machine learning suite (Vertex

AI, BigQuery, etc.).

- Core Skills: Exceptional problem-solving abilities combined with strong

communication and collaboration skills for customer-facing environments.

Valuable to Have (Preferred Qualifications)

- Google Cloud Certified Professional Machine Learning Engineer, Google Cloud

Generative AI Engineer, or TensorFlow Certified Developer certifications.

- Experience integrating ML pipelines with data processing pipelines.

📌 Ml Engineer (Hyderabad)
🏢 Mobilution It Systems
📍 Hyderabad