What ML Engineer Are You? How To Present Yourself On Your Resume

For any engineering domain, hiring managers will typically look at two sets of skills: technical skills and leadership skills.

For example, technical skills can be:

• Programming and Software Development

• Machine Learning depth

• Mathematics and Statistics

• Big Data Technologies

• Model Deployment and MLOps

and leadership skills can be:

• Team Collaboration

• Communication Skills

• Strategic Thinking

• Execution

• Adaptability

Depending on how you write your resume, hiring managers intuitively categorize the candidates into different engineering personas:

For example, let’s look at the following description of job responsibilities:

Machine Learning Engineer at [Company]: June 2020 to Present

Contributed to the development and refinement of machine learning models at [Company], focusing on improving accuracy and efficiency. Assisted in the deployment of a predictive analytics tool that increased customer retention rates by 15%. Gained proficiency in Python, TensorFlow, and cloud computing services, demonstrating a rapid learning curve and a strong commitment to contributing to team goals.

This description displays low technical skills and low leadership skills! This description showcases a learning-oriented approach with a focus on contributions to projects and skill acquisition. Highlighting assistance in deployment, proficiency gains in key technologies, and contributions to team goals without leading the projects directly caters to an entry-level or junior profile. It speaks to a persona that is in the early stages of their career, eager to learn, and rapidly developing their technical skills, hence "emerging talent."

Now let’s look at the following one:

Machine Learning Engineer at [Company]: June 2020 to Present

Specialized in deep learning and natural language processing at [Company], developing state-of-the-art models that enhanced the core product's capabilities. Published two papers in top-tier AI conferences on innovative approaches to model training that minimizes computational resources without sacrificing performance. Led the technical design and implementation of an AI-driven recommendation system that boosted user engagement by 40%.

Clearly, it showcases high technical skills but low leadership skills! Focusing on deep specialization in areas like deep learning and NLP, innovative model training approaches, and significant contributions to the field through publications, this description aligns with an expert engineer persona. It portrays a candidate who not only excels in their technical niche but also contributes to advancing the field. The mention of leading the technical design of major projects underscores their role as a key technical contributor or specialist within their domain rather than a broad-based leader or manager.

Now let’s look at the following one:

Machine Learning Engineer at [Company]: June 2020 to Present

Leveraged machine learning insights to guide strategic decision-making and enhance product innovation at [Company]. Led cross-functional teams in integrating AI capabilities into existing platforms, significantly improving user engagement by 25% within the first year. Acted as a bridge between technical teams and executive management to ensure alignment with corporate objectives, driving the adoption of AI across business processes.

Here, we have low technical skills and high leadership skills! This description focuses on strategic impact and leadership beyond the technical aspects of machine learning. It highlights the candidate's ability to leverage ML insights for strategic business decisions, lead cross-functional teams, and facilitate the integration of AI with corporate objectives. The emphasis on improving user engagement and driving AI adoption across business processes showcases a broader vision and strategic thinking, characteristic of a leader who can navigate both technical and business landscapes without needing to delve into technical specifics.

And now, this last one:

Machine Learning Engineer at [Company]: June 2020 to Present

Oversaw the machine learning team at [Company], directing project initiatives from conception to deployment with a keen focus on scalable solutions. Mentored junior engineers, fostering a collaborative environment that accelerated the team’s delivery speed by 30%. Designed and implemented a robust ML pipeline that reduced model training time by 50%, enhancing the team's ability to rapidly iterate and deploy AI models in production environments.

Here, we have a strong candidate! The emphasis here is on technical oversight, team leadership, and process improvement, signaling a role that is hands-on with technology while also managing a team. Mentioning mentoring, accelerating delivery speed, and implementing a robust ML pipeline indicates a blend of technical mastery and leadership. This persona is responsible for guiding the technical direction and ensuring the team's productivity and growth, indicative of someone who leads by example in both technical and managerial capacities.