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Staff Machine Learning Engineer (7-10 years of experience)

Outreach Corporation

Job Overview

Location

Hyderabad

Job Type

Full-time

Full Job Description

📋 Description

• Join Outreach Corporation as a Staff Machine Learning Engineer and play a pivotal role in shaping the future of our AI Revenue Workflow Platform. With 7-10 years of experience, you will be instrumental in driving innovation and delivering cutting-edge machine learning solutions that empower our customers' sales teams. Outreach is not just another company; we are the pioneers of the only complete AI Revenue Workflow Platform, designed to provide sales leaders with unparalleled connected account visibility, actionable performance insights, and highly accurate forecasting across all Go-To-Market (GTM) teams. Our platform infuses agentic AI to power hundreds of critical use cases across the entire sales motion, from identifying and acquiring new logos to managing renewals and expansions. By automating complex workflows, Outreach empowers sales professionals to dedicate their time to more strategic conversations and impactful actions, ultimately driving revenue growth.
• As a Staff Machine Learning Engineer, you will be a key contributor to our data-driven strategy, which is fundamental to both our success and that of our customers. Data is the lifeblood of Outreach, informing everything from customer health scores and revenue dashboards to the operational efficiency of our infrastructure. You will leverage this data to enhance product engagement and user productivity through advanced Natural Language Understanding (NLU) techniques, and to develop sophisticated predictive analytics and causal inference models through rigorous experimentation. Your work will directly impact how we understand our customers' needs more deeply and how we deliver new products and features that continuously refine their customer engagement workflows.
• The Data Science team at Outreach is on a mission to enable continuous optimization of customer engagement workflows. This involves reconstructing these complex workflows from vast datasets, developing robust metrics to quantify the success and efficiency of these workflows, and building intuitive tools that empower our users to optimize their processes. As a Staff ML Engineer, you will collaborate closely with a talented group of data scientists, fellow machine learning engineers, and application engineers. Together, you will define, implement, and iterate on our strategy, ensuring we consistently deliver on our mission to provide unparalleled value to our customers.
• Your responsibilities will span the entire machine learning lifecycle. This includes conceptualizing and designing novel ML models, developing robust data pipelines for training and inference, implementing and deploying these models into production environments, and continuously monitoring and iterating on their performance. You will be expected to tackle complex challenges, such as improving the accuracy of our forecasting models, enhancing the effectiveness of our prospecting tools through intelligent lead scoring, and developing new agentic AI capabilities that automate tasks and provide proactive recommendations.
• You will have the opportunity to work with state-of-the-art technologies and methodologies. This includes deep learning frameworks, large language models (LLMs), reinforcement learning, and advanced statistical modeling techniques. You will be responsible for evaluating and selecting appropriate algorithms and tools, ensuring scalability and efficiency in our ML systems, and maintaining high standards for code quality, testing, and documentation.
• Beyond technical contributions, you will act as a technical leader and mentor within the team. You will share your expertise, guide junior engineers, and contribute to architectural decisions. Your insights will be crucial in identifying new opportunities to apply machine learning to solve business problems and enhance our product offerings. You will also engage with cross-functional teams, including product management and engineering, to translate business requirements into technical solutions and ensure alignment on project goals and timelines.
• This role offers a unique chance to make a significant impact on a rapidly growing company that is revolutionizing the sales technology landscape. You will be at the forefront of AI innovation, working on challenging problems with real-world applications that drive tangible business outcomes for some of the world's leading organizations. If you are a passionate and experienced Machine Learning Engineer looking for an opportunity to lead, innovate, and grow, Outreach is the place for you.

🎯 Requirements

• Minimum of 7 years of professional experience in Machine Learning Engineering, with a proven track record of designing, building, and deploying ML models in production environments.
• Strong proficiency in Python and common ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Deep understanding of ML algorithms, statistical modeling, and data mining techniques, with experience in areas like Natural Language Processing (NLP), predictive modeling, and recommendation systems.
• Experience with large-scale data processing and distributed computing frameworks (e.g., Spark, Hadoop).
• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.

🏖️ Benefits

• Competitive salary and equity package.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and holidays.
• Opportunities for professional development and continuous learning.
• Collaborative and innovative work environment.

Skills & Technologies

Senior

Onsite

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Outreach Corporation

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About Outreach Corporation

Outreach Corporation provides a sales execution platform that streamlines prospecting, deal management, and forecasting for B2B teams. The cloud software integrates email, voice, social, and meeting workflows, automates sequences, and surfaces AI-driven insights to improve rep productivity and revenue predictability. Founded in 2014 and headquartered in Seattle, it serves mid-market and enterprise customers worldwide.

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