AI Engineer

Role: AI Engineeer

Experience: 8+ Years

Location: Kochi (Hybrid)

Notice Period: Immediate

Requirements: 

• Educational Background: 

·       Bachelor's degree in computer science, engineering, mathematics, statistics, or a related field. Advanced degrees such as  Master's or Ph.D. are preferred. 

·       Specialization or coursework in artificial intelligence, machine learning, deep learning, data science, or related fields. 

• Technical Skills: 

·       Proficiency in programming languages commonly used in AI and machine learning, such as Python, R, Java, or C++. 

·       Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques. 

·       Experience with deep learning frameworks such as Tens or Flow, PyTorch, or Keras. 

·       Knowledge of natural language processing (NLP), computer vision, and other AI-related domains relevant to health tech applications. 

·      Familiarity with data pre-processing, feature engineering, and model evaluation techniques. 

·       Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and distributed computing frameworks. 

·       Understanding of software development methodologies, version control systems (e.g., Git), and agile practices. 

• Domain Knowledge: 

·       Understanding of healthcare industry standards, regulations (e.g., HIPAA), and best practices related to data privacy, security, and compliance. 

·       Knowledge of healthcare data sources and formats, including electronic health records (EHRs), medical imaging data, wearable sensor data,  and genomic  data. 

·       Familiarity with healthcare terminology, clinical workflows, and patient care processes. 

• Problem-Solving Skills: 

·       Ability to analize complex problems, identify opportunities for AI-driven solutions, and develop innovative approaches to address them. 

·       Strong analytical and critical thinking skills, with the ability to interpret data, draw insights, and make data-driven decisions. 

·       Experience with experimental design, hypothesis testing, and model validation techniques. 

• Communication and Collaboration: 

·       Excellent communication skills, with the ability to effectively communicate technical concepts to non-technical stakeholders. 

·       Experience working in cross-functional teams, collaborating with clinicians, healthcare professionals, software engineers, and other stakeholders. 

·       Ability to work in a fast-paced, dynamic environment, adapt to changing priorities and prioritize tasks effectively. 

• Continuous Learning and Professional Development: 

·       Demonstrated commitment to continuous learning and professional development, staying abreast of the latest advancements in AI, machine learning, and health tech. 

·       Participation in relevant conferences, workshops, online courses, and community events to expand knowledge and skills in AI and healthcare. 

• Ethical and Responsible AI Practices: 

·       Commitment to ethical and responsible AI practices, including fairness, transparency, accountability, and bias mitigation. 

·       Understanding of ethical considerations and regulatory requirements related to AI applications in healthcare, including patient consent, data privacy, and algorithmic transparency. 

Responsibilities: 

• Develop and implement AI algorithms and models to analyse healthcare data, including electronic health records
• (EHRs), medical imaging data, wearable sensor data, and genomic data. 
• Design and optimize machine learning pipelines for data pre-processing, feature extraction, model training, and evaluation, ensuring scalability, performance, and reliability. 
• Collaborate with clinicians,healthcare professionals, and domain experts to understand clinical requirements, validate AI models, and integrate AI-driven solutions into clinical workflows. 
• Conduct exploratory data analysis, identify patterns, trends, and insights in healthcare data, and translate findings into actionable recommendations and decision support tools. 
• Explore and experiment with emerging AI technologies, frameworks, and tools to drive innovation and continuous improvement in AI capabilities. 
• Ensure compliance with regulatory requirements, data privacy standards, and ethical guidelines related to AI applications in healthcare, including HIPAA and GDPR. 
• Collaborate with software engineers, data scientists, and other stakeholders to deploy AI models into production environments, monitor performance, and iterate on solutions based on feedback. 
• Participate in code reviews, knowledge sharing sessions, and cross-functional team meetings to foster collaboration, learning, and best practices in AI development. 
• Stay abreast of the latest advancements in AI, machine learning, and health tech by actively participating in conferences, workshops, and professional development activities. 
• Contribute to the research community by publishing papers, presenting findings at conferences, and participating in open-source projects related to AI in healthcare. 

Skills Required:

• Bachelor's degree or higher in computer science, engineering, mathematics, statistics, or a related field. 
• Advanced degrees (Master's or Ph.D.) are preferred. 
•  Minimum of 5 years of experience in AI engineering, machine learning, or data science, with a focus on healthcare applications. 
•  Proficiency in programming languages commonly used in AI and machine learning, such as Python, R, Java, or C++.