Freshers Hiring! Begin Your Journey as a Machine Learning Engineer at HARMAN International!
Company : HARMAN International (A Samsung Company)
Position: Machine Learning Engineer
Location: Pune , Bangalore , Gurgaon , Coimbatore
Experience : Freshers
Qualification : Graduation
Salary : As per Company Standards
Last Date : Apply as soon as possible
Responsibilities:
The responsibilities of a candidate involves supporting the design, development, and implementation of machine learning models and algorithms. A candidate will have to collaborates with cross-functional teams to understand business requirements and transforms these into technical solutions that align with organizational goals. A candidate are involved in preprocessing and analyzing large datasets to uncover meaningful insights and identify patterns that can guide decision-making processes.
A important part of the role is performing tasks such as data cleaning, feature engineering, and data augmentation to enhance the accuracy and efficiency of machine learning models. A candidate conducts experiments to test hypotheses, compares different machine learning techniques, and evaluates their performance to determine the most effective approach for a given problem.
Additionally, A candidate will be responsible for implementing and optimizing machine learning pipelines to ensure that a candidate are efficient and scalable. This includes structuring workflows and processes that allow for smooth integration of data, models, and systems. Once developed, the machine learning models are deployed into production environments, where a candidate monitors their performance and makes necessary adjustments to maintain effectiveness over time.
Documentation is an important task of the role. A candidate ensures that methodologies, processes, and results are clearly recorded to enable reproducible and facilitate knowledge sharing within the organization. This helps build a strong foundation for ongoing learning and collaboration among team members.
Staying updated with the latest advancements in machine learning and related technologies is also a important responsibility. By continuously improving their knowledge, A candidate ensures that the solutions provided are innovative and make use of the best available tools and techniques.
Through candidates efforts, A candidate plays a important role in driving the organization’s data-driven initiatives, enhancing operational efficiency, and supporting strategic decision-making with cutting-edge machine learning applications.
Eligibility Criteria:
A candidate should hold a bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. A candidate should have 0–2 years of experience in machine learning, Generative AI, Deep Learning, and Natural Language Processing, showcasing their foundational knowledge and growing expertise in these fields.
A strong understanding of statistical modeling, machine learning, and data mining techniques is necessary . This needs familiarity with concepts such as supervised and unsupervised learning, regression, classification, clustering, and neural networks. A candidate should demonstrate a solid grasp of these methods and how a candidate can be applied to solve real-world problems.
Proficiency in programming languages, particularly Python, is necessary for a candidate. A candidate should also have hands-on experience with open-source machine learning and Generative AI tools and frameworks, such as PyTorch, Keras, Scikit-learn, LangChain, LlamaIndex, ChromaDB, and Qdrant. This technical expertise ensures that candidate can effectively contribute to developing and implementing machine learning models and pipelines.
Problem-solving is a key strength of a candidate, with the ability to think critically and approach challenges creatively. A candidate analytical mindset enables them to identify effective solutions and innovate in their work. Strong communication and presentation skills are equally important, as a candidate must be able to explain complex concepts in a clear and accessible manner to both technical and non-technical audiences.
The ability to work both independently and collaboratively is essential for success in this position. A candidate should thrive in a fast-paced and dynamic environment, managing their tasks efficiently while contributing to team efforts. Flexibility and adaptability are important traits as a candidate navigate evolving priorities and technologies.
Internship or project experience related to machine learning or data science is highly valued. This hands-on exposure helps demonstrate a candidate’s practical skills and ability to apply theoretical knowledge in real-world settings. Additionally, a project portfolio with multiple real-life projects, including personal or pet projects, is a significant asset. This showcases candidate initiative, creativity, and technical capabilities, providing concrete evidence of their expertise and passion for the field.
Overall, A candidate combines technical knowledge, practical experience, and soft skills to effectively contribute to machine learning and data science initiatives. A candidate show promise in leveraging their skills to create meaningful solutions and drive innovation within their role.
Preferred Skills :
A candidate has experience with big data tools and platforms, including Hadoop, Spark, or Hive. These tools enable a candidate to work with and process large datasets effectively, making them proficient in handling complex data tasks.
A candidate must also experienced with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. This knowledge allows candidates to leverage cloud resources for data storage, processing, and deploying applications, ensuring scalability and efficiency in their work.
A candidate must be familiar with both SQL and NoSQL databases, demonstrating their ability to work with structured and unstructured data. This versatility ensures a candidate can manage diverse data storage and retrieval needs effectively, depending on the project requirements.
An understanding of software development best practices is another important skill. A candidate is proficient in version control tools like Git, which help maintain organized and collaborative workflows in development teams. Additionally, A candidate should be familiar with Agile methodologies, allowing them to contribute effectively in dynamic and iterative development environments.
Such skills reflect a candidate’s technical proficiency and ability to adapt to modern tools and practices. A candidate expertise in big data, cloud platforms, databases, and development methodologies positions them to contribute meaningfully to data-driven projects and collaborative software development efforts.