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Product Development Engineer I - Machine Learning - Job Opportunity at Phenom People

Hyderabad, India
Full-time
Entry-level
Posted: June 9, 2025
On-site
USD 15,000 - 25,000 per year (INR 12-20 lakhs annually) based on entry-level ML engineer positions in Hyderabad's tech sector, with potential for rapid increases given the company's unicorn status and growth trajectory

Benefits

Flexible scheduling arrangements that provide work-life balance and accommodate diverse personal needs, positioning the company as progressive in employee welfare
Comprehensive health insurance coverage ensuring medical security and reducing personal healthcare costs, demonstrating commitment to employee wellbeing
Career development pathways with structured growth opportunities in a rapidly expanding global organization
Performance-based perks and location-specific benefits that enhance overall compensation package beyond base salary

Key Responsibilities

Design and implement cutting-edge machine learning algorithms that directly impact product performance and user experience, positioning yourself as a key technical contributor to AI-driven talent solutions
Lead cross-functional collaboration initiatives to translate complex business requirements into scalable technical solutions, demonstrating strategic thinking and business acumen
Drive innovation through continuous research and implementation of latest ML advancements, establishing yourself as a thought leader in HR technology applications
Transform large-scale data analysis into actionable insights that shape product strategy and enhance user engagement across the talent experience platform
Architect and maintain robust ML pipelines that ensure reliable, scalable deployment of AI solutions in production environments
Collaborate with senior stakeholders including product managers and designers to deliver high-impact features that drive business growth and user satisfaction
Contribute to engineering excellence through comprehensive code reviews and technical mentorship, building a culture of quality and continuous improvement
Resolve complex technical challenges related to ML model performance and optimization, demonstrating problem-solving expertise in mission-critical systems
Communicate technical solutions effectively to diverse stakeholders, bridging the gap between advanced AI concepts and business value creation

Requirements

Education

Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Experience

0-3 years of experience in developing and implementing machine learning algorithms and models

Required Skills

Strong understanding of machine learning concepts and techniques such as supervised and unsupervised learning, deep learning, and natural language processing Proficiency in programming languages such as Python Experience with machine learning frameworks such as PyTorch, Transformers, TensorFlow or Keras Knowledge of data processing and analysis tools such as SQL, Spark, or Hadoop Knowledge of Transformers, Language Models, LLMs, AI Agents Excellent problem-solving and analytical skills Strong communication and collaboration skills Ability to work in a fast-paced and dynamic environment
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Sauge AI Market Intelligence

Industry Trends

The HR technology sector is experiencing unprecedented growth driven by AI adoption, with companies investing heavily in talent experience platforms to address post-pandemic workforce challenges and the increasing importance of employee experience in retention strategies. Large Language Models and AI agents are revolutionizing HR tech, enabling personalized candidate experiences, automated screening processes, and intelligent talent matching, creating high demand for ML engineers who can implement these technologies in production environments. The Indian tech hub market, particularly Hyderabad, has become a strategic location for global HR tech companies seeking top-tier AI talent while maintaining cost efficiency, leading to increased competition for skilled ML engineers in the region.

Role Significance

Likely part of a 5-8 person ML engineering team within a larger product development organization, with opportunities to work closely with data scientists, product managers, and senior engineers across multiple time zones
Individual contributor role with high growth potential, positioned as a foundational engineering role that offers direct exposure to cutting-edge AI applications and cross-functional collaboration with senior stakeholders in a unicorn environment

Key Projects

Implementation of AI-powered candidate matching algorithms that improve placement success rates Development of conversational AI agents for candidate engagement and automated screening processes Creation of predictive analytics models for talent pipeline optimization and workforce planning Integration of large language models for resume parsing, job description optimization, and personalized content generation

Success Factors

Rapid adaptation to evolving AI technologies, particularly in the NLP and LLM space, as the HR tech industry continues to integrate more sophisticated language understanding capabilities into talent experience platforms. Strong collaboration skills across global teams, as success in this role requires effective communication with stakeholders across different time zones and cultural contexts in Phenom's international organization. Business acumen to understand HR workflows and talent acquisition challenges, enabling the translation of complex technical capabilities into practical solutions that address real-world recruitment and employee experience problems. Continuous learning mindset to stay current with the rapidly evolving ML landscape, particularly as new model architectures and training techniques emerge that could provide competitive advantages in talent matching and engagement.

Market Demand

Very High - The intersection of AI/ML expertise and HR technology represents one of the fastest-growing segments in enterprise software, with particularly strong demand for engineers who can work with modern NLP and LLM technologies

Important Skills

Critical Skills

Python proficiency is absolutely essential as it serves as the primary language for ML development, data processing, and integration with existing systems. Strong Python skills enable rapid prototyping, efficient model development, and seamless collaboration with data science teams working on similar technology stacks. Deep learning and NLP understanding is crucial given the text-heavy nature of HR data including resumes, job descriptions, and candidate communications. This knowledge directly translates to building more effective talent matching algorithms and automated screening processes that form the core of Phenom's value proposition. Experience with modern ML frameworks, particularly PyTorch and Transformers, is critical as these tools are fundamental to implementing the large language models and AI agents that represent the cutting edge of HR technology innovation and competitive differentiation.

Beneficial Skills

Knowledge of distributed computing tools like Spark and Hadoop becomes increasingly valuable as data volumes grow and real-time processing requirements intensify in enterprise HR applications serving millions of users globally. Understanding of MLOps practices and deployment pipelines, while not explicitly mentioned, is highly beneficial for ensuring reliable production deployment of AI models in enterprise environments where downtime directly impacts client operations and revenue. Familiarity with cloud platforms and containerization technologies would accelerate contribution to scalable AI infrastructure, particularly important for a global platform that needs to handle varying loads across different geographic regions and time zones.

Unique Aspects

Entry-level opportunity to work with state-of-the-art LLM and AI agent technologies in a production environment serving millions of users, providing accelerated learning and career development typically not available at this experience level.
Direct exposure to the intersection of AI and human resources, a rapidly growing field that combines technical complexity with high business impact, offering unique expertise that is increasingly valuable across industries.
Opportunity to contribute to a platform that genuinely impacts career outcomes for millions of job seekers globally, providing meaningful work that combines technical excellence with social impact in the employment ecosystem.
Access to unicorn-level resources and mentorship while working in a cost-effective location, creating an optimal environment for rapid professional growth and skill development in cutting-edge AI applications.

Career Growth

18-24 months to senior individual contributor level, 3-4 years to team leadership roles, given the rapid growth environment and high-impact nature of AI work in the HR tech space

Potential Next Roles

Senior ML Engineer with specialization in HR technology applications ML Team Lead managing cross-functional AI initiatives Product Manager for AI-powered talent experience solutions Principal Engineer architecting ML infrastructure for global HR platforms

Company Overview

Phenom People

Phenom People operates as a leading AI-powered talent experience platform serving global enterprises, having achieved unicorn status through rapid growth and innovation in the HR technology sector, with a strong focus on applying artificial intelligence to solve complex talent acquisition and employee experience challenges.

Well-established market leader in the talent experience platform space, competing with companies like SmartRecruiters and Greenhouse, but differentiated through heavy investment in AI capabilities and global enterprise client base spanning multiple industries.
Hyderabad serves as a key development hub for Phenom's global operations, leveraging India's strong AI/ML talent pool while maintaining 24/7 development cycles across their six-country presence, providing exposure to international projects and career mobility opportunities.
Fast-paced, innovation-driven environment typical of unicorn companies, with emphasis on rapid iteration, cross-functional collaboration, and cutting-edge technology implementation, balanced with structured processes needed to serve enterprise clients reliably.
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