Artificial Intelligence Engineer and Data Science Specialist

4 weeks ago

Bengaluru, India BlinkLink Full time

Company Description

Blinklink is an AI company focused on democratizing content distribution and curation infrastructure. We enable our customers to add full-scale short-form video platforms to any website in 5 minutes. Platforms can curate content libraries uniquely for each visitor based on algorithms created in natural language. Audiences are key in the attention economy, and companies use Blinklink to build and scale true ownership and monetization over their audience.


BlinkLink is headquartered in Pittsburgh and is accelerated by Carnegie Mellon University.


Why this is/is not for you

You're looking for a post-PMF AI company with a clear trajectory, "difficult" AI problems, and an extremely complementary, seriously experienced, and mission-devoted team.


Key Responsibilities:

  • Algorithm Development and Implementation: Design, develop, and implement cutting-edge AI/ML algorithms and models to solve complex business problems. This includes prompt engineering, data preprocessing, feature engineering, model selection, training, validation, and deployment.
  • Data Analysis and Interpretation: Analyze large volumes of structured and unstructured data to extract meaningful insights and patterns. Utilize statistical methods, machine learning techniques, and data visualization tools to interpret results and communicate findings to stakeholders.
  • Model Evaluation and Optimization: Evaluate the performance of AI/ML models using appropriate metrics and techniques. Fine-tune model parameters, optimize algorithms and conduct experiments to improve accuracy, efficiency, and scalability.
  • Data Engineering and Integration: Collaborate with data engineers and IT professionals to acquire, preprocess, and integrate data from multiple sources. Ensure data quality, consistency, and integrity throughout the entire data lifecycle.
  • Machine Learning Infrastructure: Build and maintain scalable and efficient machine learning infrastructure, including model training pipelines, deployment pipelines, and monitoring systems. Leverage cloud services, containerization, and orchestration tools for seamless integration and automation.
  • Research and Innovation: (Read) Stay abreast of the latest developments in AI/ML research, methodologies, and technologies. Explore new algorithms, frameworks, and tools to enhance predictive accuracy, robustness, and adaptability.
  • Cross-functional Collaboration: Work closely with cross-functional teams, including software engineers, product managers, and domain experts, to understand business requirements and translate them into actionable solutions. Collaborate on interdisciplinary projects and contribute to a culture of innovation and continuous improvement.
  • Documentation and Reporting: Clearly and organizedly document code, algorithms, experiments, and findings. Prepare technical reports, presentations, and documentation for internal stakeholders, external clients, and regulatory compliance.


Qualifications:

  • A bachelor’s degree or higher in Computer Science, Statistics, Mathematics, Engineering, or a related field is required. An advanced degree (e.g., Master's) is also good.
  • A minimum of 4 years of hands-on experience in artificial intelligence, machine learning, deep learning, and data science is required.
  • Proficiency in programming languages such as Python, R, Java, or Scala is required. Experience with popular AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is also required.
  • Strong understanding of statistical concepts, mathematical principles, and probabilistic methods relevant to machine learning and data science.
  • Demonstrated expertise in data preprocessing, feature extraction, model selection, hyperparameter optimization, and model evaluation.
  • Experience with distributed computing, parallel processing, and big data technologies (e.g., Hadoop, Spark, Kafka) is a plus.
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) for deploying and scaling machine learning applications.
  • Excellent problem-solving skills, analytical thinking, and attention to detail. Ability to work independently as well as part of a collaborative team in a fast-paced environment.
  • Effective communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences. Experience in presenting findings and recommendations to senior management and stakeholders is desirable.
  • Proven track record of delivering high-quality AI/ML solutions that have a measurable impact on business outcomes and customer satisfaction.


Note: This job description is intended to convey information essential to understanding the scope of the position and is not an exhaustive list of skills, efforts, duties, responsibilities, or working conditions associated with it. Responsibilities may change based on business needs.

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