N #3191
Applications open
Full-Time Job
AIML
Musketsoft
About the role
Job description
Job Description
Senior AI/ML Engineer Job Title: Senior AI/
ML Engineer Experience
6+
Years Location
Gurugram Work Mode: Work from Office Employment Type:
Full-Time Salary
Best in the Market
About the Role
We are looking for an experienced Senior AI/ML Engineer with 6+ years of hands-on experience to join our team in Gurugram. The ideal candidate should have strong expertise in Artificial Intelligence, Machine Learning, Python, model development, and production deployment. Experience with Generative AI, LLMs, NLP, and modern AI frameworks will be highly preferred.
Key Responsibilities
- Design, develop, train, and deploy advanced AI/ML models.
- Lead end-to-end machine learning projects from requirement gathering to production deployment.
- Develop scalable ML pipelines and production-ready AI solutions.
- Perform data preprocessing, feature engineering, model evaluation, and optimization.
- Work on Generative AI, LLMs, NLP, and Deep Learning use cases.
- Develop and integrate AI/ML models with existing applications and REST APIs.
- Optimize models for scalability, performance, accuracy, and reliability.
- Mentor junior AI/ML engineers and provide technical guidance.
- Collaborate with software engineers, data engineers, and business teams.
- Evaluate emerging AI/ML technologies and recommend suitable solutions.
Required Skills
- 6+ years of hands-on experience in AI/ML or related technologies.
- Strong proficiency in Python.
- Strong understanding of Machine Learning and Deep Learning algorithms.
- Hands-on experience with TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
- Strong experience in data preprocessing, feature engineering, model optimization, and evaluation.
- Experience with NLP, LLMs, Generative AI, or Computer Vision.
- Strong knowledge of SQL and databases.
- Experience building and consuming REST APIs.
- Experience deploying AI/ML solutions in production environments.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Strong problem-solving, analytical, communication, and leadership skills.
- Good to Have Hands-on experience with RAG, LangChain, LlamaIndex, Hugging Face, and Vector Databases.
- Experience with OpenAI or other LLM APIs.
- Knowledge of MLOps, Docker, Kubernetes, and CI/CD.
- Experience with AWS AI/ML services.
- Experience designing scalable and highly available AI solutions.
- Prior experience leading or mentoring an AI/ML team.
Eligibility & process
Who can apply
Experience: 8-12 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
20 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for Musketsoft and tech roles.
Technical Placement Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
APTITUDE & LOGIC
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
COMPANY GUIDE
Musketsoft Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Musketsoft and off-campus tech roles.
MOCK TESTS & PAPERS
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
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 (Deep Learning, Machine, Artificial Intelligence, Aiml, Machine Learning, Python, SQL, REST APIs) & 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
Musketsoft 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 Musketsoft as a AIML?
Highlight Musketsoft's market reputation, recent tech innovations, and how your skills in Deep Learning directly solve their team's objectives.
Highlight Musketsoft's market reputation, recent tech innovations, and how your skills in Deep Learning 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).
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.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
25-32.5 Lacs PA
Gurugram, India
Experience: 8-12 Yrs. Open to matching quβ¦
