📋 Job Details at a Glance 📍 Location Gurgaon, Haryana, India 🏢 Company IBM 👥 Experience Fresher 🎓 Qualification Bachelor's Degree 📅 Eligible Batch 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary ₹6.0 – ₹9.5 LPA 🏢 Industry Technology 🛠 Key Skills Python Machine Learning TensorFlow Scikit-learn SQL NumPy Data Engineer-Machine Learning at IBM — Full Details & How to Apply IBM is seeking fresh talent for the Data Engineer-Machine Learning role in Gurgaon, Haryana, India , where you can leverage cutting-edge technologies like TensorFlow and SQL . This position offers a competitive salary range of ₹6.0 – ₹9.5 LPA , making it an attractive option for recent graduates. The demand for Data Engineer-Machine Learning jobs is surging as companies increasingly rely on machine learning to drive decision-making. This role is crucial for IBM's innovation strategy, enabling the development of advanced machine learning models that enhance product offerings and impact millions of users worldwide. Founded in 1911 , IBM employs over 350,000 people globally and is a leader in AI and cloud computing. This scale and commitment to innovation make IBM an ideal employer for aspiring data engineers, offering a culture that fosters growth and collaboration. We encourage 2024, 2025, 2026 graduates with a Bachelor's Degree to apply for this Fresher role. With a salary range of ₹6.0 – ₹9.5 LPA , this position is ideal for those looking to kickstart their careers in technology. In this role, you will gain hands-on experience with essential skills like Python , Machine Learning , Scikit-learn , and NumPy . This exposure not only sets you apart in the job market but also opens doors to advanced roles such as Machine Learning Engineer or Data Scientist within 1-2 years . 📊 Role Difficulty: Medium | Competition Level: High | Fresher Friendly: Yes NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Job Role & Responsibilities The core mission of the Data Engineer-Machine Learning role at IBM is to design and implement innovative machine learning solutions that address real-world business challenges using advanced technologies. Design and implement machine learning models using Python and TensorFlow to solve specific business problems effectively. Utilize SQL for data extraction and manipulation, ensuring data integrity and quality throughout the data lifecycle. Collaborate with data scientists and software engineers to integrate machine learning solutions into existing systems, enhancing overall functionality. Monitor model performance metrics and optimize algorithms using Python for improved accuracy and efficiency. Take ownership of data pipelines, ensuring timely and accurate data delivery for analysis and reporting. Document processes and results clearly to facilitate knowledge transfer within the team, using SQL for data documentation. Engage with clients to understand their data needs and provide tailored machine learning solutions that meet specific requirements. This role fosters an ownership culture, allowing you to make a direct impact on projects and contribute to the success of IBM through innovative data solutions. Required Skills & Technical Competencies The ideal candidate for the Data Engineer-Machine Learning role must possess a robust skill profile that includes both technical and soft skills relevant to machine learning and data engineering. Technical Skills Python — entry — essential for scripting and developing machine learning algorithms, particularly with libraries like NumPy . Machine Learning — entry — foundational knowledge required to understand and implement various algorithms effectively in real-world applications. TensorFlow — entry — used daily for building and training machine learning models, crucial for delivering effective solutions. SQL — entry — necessary for querying databases and managing data efficiently in projects, ensuring data quality. NumPy — entry — utilized for numerical computations and data manipulation within machine learning workflows. Soft Skills & Professional Competencies Problem-solving — critical for troubleshooting issues in data processing and model performance, ensuring smooth operations. Communication — essential for engaging with clients to understand their data needs and articulate technical concepts clearly. Attention to Detail — necessary for maintaining data integrity and quality throughout the data lifecycle. Adaptability — important for adjusting to new tools and technologies as they emerge in the field of machine learning. Good to Have (Bonus Skills) Familiarity with Scikit-learn — enhances your ability to implement machine learning algorithms quickly and efficiently. Exposure to cloud platforms like IBM Cloud — opens opportunities for deploying machine learning models in production environments. Understanding of data visualization tools — aids in presenting data insights effectively to stakeholders, enhancing decision-making. When showcasing these skills in your resume or interview, emphasize practical applications and relevant projects that demonstrate your proficiency and understanding of each skill. Eligibility Criteria This role is specifically designed for fresh graduates eager to start their careers in data engineering and machine learning. Candidates must hold a Bachelor's degree in Computer Science , Engineering , or a related field. Eligible batches include 2024 , 2025 , and 2026 graduates, ensuring fresh perspectives. This role is specifically tailored for freshers , making it an ideal starting point for those new to the industry. A minimum academic performance of 60% is preferred to ensure a strong foundational knowledge. Having a portfolio or GitHub showcasing relevant projects can significantly enhance your application. Documentation & Portfolio Requirements Ensure your resume is well-structured, highlighting your educational background, skills, and relevant projects. Include links to your GitHub or portfolio to showcase your work. Pro tip: Tailor your application to highlight specific projects that demonstrate your experience with Python and machine learning concepts. Salary for Data Engineer-Machine Learning at IBM 💰 Compensation ₹6.0 – ₹9.5 LPA The advertised compensation for the Data Engineer-Machine Learning role at IBM is ₹6.0 – ₹9.5 LPA . The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Selection Process at IBM The selection process for the Data Engineer-Machine Learning role at IBM is designed to assess both technical skills and cultural fit. 1 Online Assessment — 60 minutes, testing basic programming and machine learning concepts through MCQs 2 Technical Interview — focuses on Python, SQL, and machine learning algorithms, assessing practical knowledge 3 Behavioral Interview — evaluates cultural fit and problem-solving skills through situational questions 4 HR Interview — discusses salary expectations and company culture, with an offer timeline of 1-2 weeks Topic-wise Preparation Guide Round 1: Online Assessment Python basics — understanding syntax and data structures is crucial for coding tasks — LeetCode Machine Learning fundamentals — key concepts like supervised vs. unsupervised learning — Coursera SQL queries — practice writing complex queries to manipulate data effectively — W3Schools Data structures and algorithms — essential for optimizing code performance — GeeksForGeeks Round 2: Technical Interview Python libraries — focus on NumPy and Pandas for data manipulation — Khan Academy Machine Learning algorithms — depth in regression, classification, and clustering techniques — Coursera SQL optimization techniques — understanding indexing and query performance — GeeksForGeeks Data preprocessing methods — essential for preparing data for machine learning — freeCodeCamp Model evaluation metrics — familiarize with accuracy, precision, recall, and F1 score — Coursera Round 3: Behavioral Interview Behavioral questions using the STAR method — prepare scenarios demonstrating teamwork and problem-solving — MindTools Conflict resolution — discuss how to handle disagreements in a team setting — YouTube Technical deep-dive into a machine learning project you’ve worked on — Khan Academy Timeline & Expectations The application to offer timeline typically spans 1-2 weeks , allowing candidates to prepare adequately for each stage. Focus on demonstrating both your technical expertise and your ability to fit within the company culture during interviews. Expected Interview Questions for Data Engineer-Machine Learning at IBM These questions are based on the role's actual tech stack and responsibilities. Technical Questions Explain how you would implement a machine learning model using TensorFlow. What are the differences between supervised and unsupervised learning? How do you optimize SQL queries for performance? Describe a project where you used Python for data analysis. What metrics would you use to evaluate a machine learning model? How do you handle missing data in a dataset? Behavioral Questions Describe a time you worked in a team to solve a problem. How do you prioritize tasks when working on multiple projects? Tell me about a challenge you faced and how you overcame it. What motivates you to work in the field of data engineering? Role-Specific Questions What steps would you take to ensure data quality in your projects? How do you stay updated with the latest trends in machine learning? Can you explain a machine learning project you are particularly proud of? Structure your answers using the STAR method to clearly articulate your experiences and thought processes. Resume Tailoring & ATS Keywords for Data Engineer-Machine Learning Optimizing your resume for ATS is crucial for standing out in the application process. ATS Keywords to Include Data Engineer Machine Learning Python TensorFlow SQL Scikit-learn NumPy Data Analysis Model Optimization Data Pipelines Problem Solving Collaboration Resume Tips for This Role Highlight relevant coursework or projects that demonstrate your skills in Python and machine learning. Emphasize any internships or practical experiences related to data engineering or analysis. Include links to your GitHub or portfolio showcasing your projects to provide tangible evidence of your skills. Optimize your resume for ATS by using keywords from the job description. Avoid including unrelated work experience that does not demonstrate your fit for this role. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Do not include generic skills or experiences that do not relate to the Data Engineer role. About IBM IBM was founded in 1911 and has its headquarters in Armonk, New York . With a global workforce of over 280,000 employees , IBM maintains a significant presence in Gurgaon, Haryana , employing thousands in various technology roles. This extensive footprint allows IBM to serve clients across multiple industries worldwide. IBM is known for its innovative products such as IBM Cloud and Red Hat OpenShift , which are pivotal in cloud computing and container orchestration. Additionally, IBM has made significant strides in artificial intelligence with its flagship product, Watson , which revolutionizes data analysis and decision-making processes for businesses. The workplace culture at IBM has earned it numerous accolades, including consistent rankings in the top 100 companies to work for on Glassdoor. Employee programs such as the IBM Global University Program foster collaboration and innovation, ensuring that employees are engaged and supported in their career growth. Recently, IBM announced a strategic shift towards hybrid cloud services, aiming to capture a larger share of the growing cloud market. This initiative reflects IBM 's commitment to adapting to industry trends and enhancing its technological offerings, further solidifying its position as a leader in the tech sector. Joining IBM as a fresher provides unparalleled access to mentorship from industry leaders and the chance to work on groundbreaking projects. The company’s focus on innovation and technology makes it an ideal launchpad for those looking to build a successful career in the tech industry. Why Join IBM as Data Engineer-Machine Learning? At IBM , you will gain hands-on experience with cutting-edge technologies that are essential for your career development in data engineering and machine learning. Hands-on Experience with TensorFlow — work directly with a leading machine learning framework, crucial for building scalable models in real-world applications. SQL and Data Manipulation Skills — enhance your expertise in SQL and data manipulation techniques, making you a valuable asset in any tech team. Career Advancement Opportunities — after 1-2 years, transition into advanced roles like Data Scientist or ML Engineer, significantly boosting your career prospects. Collaborative Culture — benefit from a culture that encourages knowledge sharing, allowing you to learn from experienced professionals across various domains. Vibrant Lifestyle in Gurgaon — enjoy a vibrant lifestyle with excellent connectivity to Delhi, making it an ideal location for young professionals. Access to Industry Leaders — receive mentorship from industry experts, providing invaluable insights and guidance as you navigate your career path. According to NexisGrow.com, working at IBM as a Data Engineer-Machine Learning positions you at the forefront of technological innovation, offering a unique blend of professional growth and impactful projects. Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for Data Engineer-Machine Learning at IBM? Eligibility Tap to expand + Answer Candidates with Bachelor's Degree and Fresher experience are eligible. Eligible batches: 2024, 2025, 2026. ? What skills are most important for this role? Skills Tap to expand + Answer Key skills: Python, Machine Learning, TensorFlow, Scikit-learn, SQL. Strong fundamentals and practical project experience matter most. ? What is the salary for this position? Salary Tap to expand + Answer Compensation: ₹6.0 – ₹9.5 LPA. Final offer depends on skills, experience, and interview performance. ? What is the interview process at IBM? Interview Tap to expand + Answer Typically: Resume shortlisting → Online test → Technical interview(s) → HR round. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer Work mode varies by team. Confirm with HR during recruitment. ? What is the career growth path from this role? Growth Tap to expand + Answer Structured appraisals every 6–12 months. Senior roles accessible within 12–18 months based on performance. ? How do I apply? Application Tap to expand + Answer Apply via the official link in How to Apply section. Highlight: Python, Machine Learning, TensorFlow, Scikit-learn, SQL. ? Is there a probation period? Probation Tap to expand + Answer Standard 3–6 months probation. Confirmation follows successful completion. ? How to prepare for the Data Engineer-Machine Learning interview? Preparation Tap to expand + Answer (1) Core concepts of Python, Machine Learning, TensorFlow, Scikit-learn, SQL, (2) 2–3 project walkthroughs, (3) Problem-solving, (4) IBM research, (5) Clear communication. ? What is the work culture like at IBM? Culture Tap to expand + Answer Research on LinkedIn and Glassdoor for authentic employee reviews. NexisGrow.com features only verified employers. 🔗 Explore More on NexisGrow More jobs in Gurgaon Browse all Tech jobs Latest Fresher jobs More jobs at IBM Work From Home jobs Ready to Apply? Don't Miss This Opportunity! Apply only via the official link. NexisGrow.com charges zero application fees. 👉 Apply Now — Official Link NexisGrow.com does not charge any application or registration fees. Beware of fraudulent offers. Naukri ki baat, NexisGrow ke saath • NexisGrow.com