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Lead/Senior AI/ML Backend Developer

RDSolutions India

  • Hyderabad, India
  • Competitive Package
  • 5+ Years
  • Posted Yesterday
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About the role

Job Title: Lead / Senior AI/ML Developer

Employment Type: Full Time, Permanent

Position Location: Hyderabad

Qualifications: BE/B.Tech/MCA Degree in Computer Science, Engineering, or similar relevant

field

Total Experience: 10+ Years

About the Role

We are looking for a Senior AI/ML Backend Developer to build and scale the systems that power our AI features. You will develop reliable Python services, integrate applications and AI models through APIs, and use SQL Server and Databricks to manage and process large datasets.

You’ll work directly with business and R&D teams to explore ideas, build proofs of concept, and turn successful experiments into reliable cloud applications. We’re looking for someone who enjoys solving open-ended problems, learning new tools, and moving quickly from concept to production.

Key Responsibilities

  • Build scalable, secure backend services and APIs using Python web frameworks.
  • Collaborate with business and R&D teams to turn prototypes into production applications.
  • Develop scripts and processes to move, clean, and transform data between applications, SQL Server, and Databricks.
  • Optimize SQL queries and data processing to improve performance and cost efficiency.
  • Design and execute automated benchmarks to evaluate the latency, throughput, and cost efficiency of AI/ML models and backend APIs.
  • Work with cloud platforms and automation tools for testing, deployment, and monitoring.

Required Skills

  • Strong backend development, data processing, and API development skills.
  • Extensive experience with Python frameworks such as FastAPI, Flask, or Django.
  • Strong knowledge of relational databases, data modeling, and advanced SQL queries.
  • Working understanding of AI/ML concepts, including embeddings, vector search, or retrieval-augmented generation (RAG).
  • Experience benchmarking backend systems, databases, or ML model inference.
  • Experience developing and deploying cloud applications, preferably in Azure.
  • Knowledge of version control using Git and CI/CD deployment pipelines.
  • Ability to work through evolving requirements and communicate technical tradeoffs.

Preferred Experience

  • SQL Server and Databricks.
  • Integrating LLMs and other AI services into production applications.
  • Performance testing tools such as Locust, JMeter, or Python profiling tools.

Eligibility & process

Who can apply

Employment type: Full-time

Skills & stack

Python SQL Django FastAPI Flask SQL Server Azure CI/CD

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, SQL, Django, FastAPI, Flask, SQL Server, Azure, CI/CD) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion RDSolutions India Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join RDSolutions India as a Lead/Senior AI/ML Backend Developer?
Highlight RDSolutions India's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
RDSolutions India Competitive Package
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