ML Engineer with 7+ years in Machine Learning, AI, and LLM systems.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer Results-driven Machine Learning Engineer with 6+ years of experience in designing, developing, and deploying AI- driven applications across various industries. Proficient in full-stack development, microservices, and cloud infrastructure with a consistent record of enhancing system performance and reducing bugs. Adept in leading cross-functional teams, mentoring junior engineers, and delivering scalable, high-performance solutions. Proven ability to implement cutting-edge machine learning models, including LLMs and ASR systems, with strong collaboration and agile development skills.
Anglia Ruskin University Cambridge
Masters in Computer Science · Computer Science
August 1, 2017 – June 30, 2019
BuzzSols
Lead Machine Learning Engineer
January 1, 2024 – Present
India
SphereSoftwareLabs
Senior Software Engineer
January 1, 2021 – January 1, 2024
India
Quinnox
Software Developer
January 1, 2019 – January 1, 2021
India
Developed a doctor-patient scheduling platform
June 9, 2026 – Present
Improved scheduling efficiency by {30%} through the development of an AI-driven doctor-patient platform.
Integrated Apache Kafka
June 9, 2026 – Present
Boosted real-time threat detection capabilities by 30% by integrating Apache Kafka for data streaming. Improved data pipeline efficiency, increasing processing speed by 25%.
Built an AI-powered email generation tool
June 9, 2026 – Present
Improved user engagement by 20% by developing an AI-powered email generation tool enhancing communication efficiency.
Cultural Fit Analysis
The candidate's diverse project experience across different industries (healthcare, finance, legal) and their involvement in both startup (BuzzSols) and larger corporate environments (SphereSoftwareLabs, Quinnox) suggest adaptability. Their leadership role and emphasis on team collaboration align well with a culture that values teamwork and mentorship. The focus on improving efficiency and reducing bugs across projects indicates a results-driven mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, team collaboration, and agile development skills through their experience leading teams and managing deliverables. Their ability to translate business goals into ML solutions indicates strong problem-solving and stakeholder communication skills. The adoption of microservices and data-efficient pipelines suggests a focus on operational efficiency and scalability.