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Machine Learning Engineer

2 months ago

Bengaluru, India Velocity FinCrime Solutions Suite Full time

As a Machine Learning Engineer, your primary responsibility will be to design, develop, and implement machine learning models and algorithms to address complex business problems and enhance our products and services. You will work closely with data scientists, software engineers, and product managers to deploy machine learning solutions into production systems. Your expertise in machine learning will play a crucial role in driving data-driven decision-making and improving our organization's overall performance.


Key Accountabilities:


  • Lead the design, development, and optimization of machine learning models and algorithms to solve specific business challenges.
  • Collaborate with data scientists and domain experts to understand requirements and translate them into effective machine learning solutions.
  • Demonstrate fluency in various artificial intelligence and machine learning techniques, including but not limited to Linear Regression, Logistic Regression, Classification and Regression Trees, Naïve-Bayes, Clustering, and K-Nearest Neighbors.
  • Understand the appropriate application of each algorithm based on the problem domain.
  • Apply knowledge and understanding of statistics, neural networks, heuristics, Markov models, and Natural Language Processing (NLP) to address complex data challenges and develop innovative solutions.
  • Utilize R and Python languages proficiently for data manipulation, model development, and analysis.
  • Familiarity with ML frameworks, such as Keras, TensorFlow, or PyTorch, to implement and optimize machine learning models.
  • Utilize ML libraries like NumPy, Scikit-learn, Pandas, NLTK, and SpaCy to streamline the data processing and model development workflow.
  • Cleanse, pre-process, and analyse raw data to ensure its quality and suitability for machine learning applications.
  • Identify relevant features and engineer them to enhance model performance.
  • Conduct thorough testing, validation, and evaluation of machine learning models using appropriate metrics and statistical methods.
  • Implement techniques like cross-validation to ensure robust performance.
  • Deploy production-ready machine learning solutions into real-world applications and platforms.
  • Collaborate with software engineers to integrate models into existing systems and ensure scalability and reliability.
  • Stay abreast of the latest advancements in machine learning and data science techniques, tools, and libraries.
  • Proactively explore and propose the adoption of new technologies and methodologies to improve existing processes.
  • Create clear and comprehensive documentation for all developed models, algorithms, and processes.
  • Facilitate knowledge sharing and provide technical guidance to team members.
  • Adhere to data privacy and security best practices when handling sensitive or confidential information.
  • Ensure compliance with relevant regulations and company policies.
  • Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand requirements, provide insights, and drive the successful integration of machine learning solutions.
  • Participate in research projects, experiments, and proofs of concept to explore new machine learning approaches and their potential impact on the organization.


Skills and Knowledge:


  • Bachelor’s degree in Computer Science or related field with 5+ years of software development experience OR MS/PhD in CS or equivalent with 2+ yrs. of experience
  • Experience with all phases of development, including design, implementation, and operation of production systems
  • Experience in developing high-performance, highly available and scalable distributed systems
  • Should be very well versed with Python programming language
  • In-depth knowledge and fluency in a high-level programming language C/C++ and C#
  • Experience with relational and NoSQL databases
  • Solid understanding of Object-Oriented design and concepts
  • Strong analytical and problem-solving skills
  • Experience with Machine Learning
  • Experience developing software in a Unix/Linux environment